FairPlay Sports Media is seeking a data scientist to translate complex data into actionable strategies. You will partner with Product, Engineering, Marketing, and Operations to build predictive frameworks and uncover growth opportunities. Responsibilities include experimentation, predictive analytics, EDA, feature definition, and cross-functional collaboration. The role also involves designing autonomous AI agents and maintaining data pipelines with Data Engineering.
Oct 08, 2026
Full time
FairPlay Sports Media is seeking a data scientist to translate complex data into actionable strategies. You will partner with Product, Engineering, Marketing, and Operations to build predictive frameworks and uncover growth opportunities. Responsibilities include experimentation, predictive analytics, EDA, feature definition, and cross-functional collaboration. The role also involves designing autonomous AI agents and maintaining data pipelines with Data Engineering.
Data Scientist - onsite London - PhD required Job Category: Indiv Contributor-Slry Requisition Number: DATAS003457 Posted : September 9, 2026 Full-Time On-site Locations Showing 1 location London, UK W1W7NY, GBR Description WELLTOWER - REIMAGINE REAL ESTATE WITH US At Welltower, we're transforming how the world thinks about senior living and wellness-focused real estate. As a global leader in residential wellness and healthcare infrastructure, we create vibrant, purpose-driven communities where housing, healthcare, and hospitality converge. Our culture is fast-paced, collaborative, and endlessly ambitious-guided by our mantra: The only easy day was yesterday. We're looking for bold, independent thinkers who thrive on challenge, embrace complexity, and are driven to deliver long-term value. Every team member is empowered to think like an owner, innovate fearlessly, and lead from where they stand. If you're passionate about outcomes and inspired by the opportunity to shape the future of healthcare infrastructure, we want you on our best-in-class team. ABOUT THE ROLE The Data Scientist will work with the current Data Science team in the US/Canada, along with the investment/asset management team in the UK, and integrate information from various sources and analyze it for better understanding about how the business performance can be enhanced, and to analyze output from AI and ML tools that automate certain processes for capital allocation in the UK. The Data Scientist will report to the Lead Data Scientist in the US/Canada and have a dotted line to the Head of Investment in the UK, and will help us discover the information hidden in vast amounts of data, and help us make smarter investment and asset management decisions. The primary focus of this role will be in applying machine learning and predictive analytics techniques, doing statistical analysis, and building high-quality prediction systems integrated with our business model. This role will support and challenge the investment and asset management team in understanding locations across the UK where we have potential deals and where we will manage our existing assets. KEY RESPONSIBILITIES Assist the Business Insights team with Welltower's data and analytics strategy and predictive analytics application for UK asset management and investment teams Work with the investment and asset management team to guide them to the right location/market based on the data science platform Selecting features, building and optimizing classifiers using machine learning techniques Extending company's data with third party sources of information as and when needed and integrate the third-party data into the Welltower data science models Analyzing the output of the predictive analytics model to make meaningful information valuable to UK investment process and challenge the UK investment team's thesis with data backed analysis Enhancing data collection procedures to include information that is relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc analysis and presenting results to the UK team OTHER DUTIES Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, and responsibilities that are required of this employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. TRAVEL Minimal travel should be expected. MINIMUM REQUIREMENTS Experience: Knowledge of data and analytics landscape and with at least 2 years of work experience Strong technical skills to include a deep understanding of (but not limited to): Reporting and Analytical Analysis, Predictive Modeling, and Solution Architect Excellent understanding of machine learning techniques and algorithms, such as Tree Based Models, Neural Networks, etc. Experience with common data science toolkits, such as R, MatLab, Python etc. Excellence in at least one of these is highly desirable Experience with data mining and data visualization tools, such as Alteryx, Tableau, PowerBI etc. Applied statistics skills, such as distributions, correlation, statistical testing, regression, etc. Excellent verbal and written communication skills with business and technology partners. Familiarity with Real Estate, Finance and/or Healthcare industries systems and specialist in business consolidation in diverse source systems. Knowledge of enterprise profitability and business planning and forecasting. Education: PhD or Masters in Mathematics, Statistics, Economics, or Financial Analysis with a focus on Predictive Analytics solution. Background in Computer Science, Information Systems, Engineering, Statistics or related field is required. Employment is contingent upon the successful completion of a background check and verification of employment, education, and other credentials relevant to the position. WHAT WE OFFER Competitive Base Salary + Annual Bonus Generous Paid Time Off and Holidays Employee Stock Purchase Program - purchase shares at a 15% discount Pension Scheme + Profit Sharing Program Tuition Assistance Program Comprehensive and progressive Medical/Dental/Vision options Professional Growth And much more! ABOUT WELLTOWER Welltower Inc. (NYSE: WELL) an S&P 500 company, is the world's preeminent residential wellness and healthcare infrastructure company. Our portfolio of 1,500+ Seniors and Wellness Housing communities is positioned at the intersection of housing, healthcare, and hospitality, creating vibrant communities for mature renters and older adults inthe United States,United Kingdom, andCanada. We also seek to support physicians in our Outpatient Medical buildings with the critical infrastructure needed to deliver quality care. Our real estate portfolio is unmatched, located in highly attractive micro-markets with stunning built environments.Yet, we are an unusual real estate organization as we view ourselves as a product company in a real estate wrapper driven by relationships and unconventional culture. Through our disciplined approach to capital allocation powered by our data science platform and superior operating results driven by the Welltower Business System, we aspire to deliver long-term compounding of per share growth and returns for our existing investors - ourNorth Star. Welltower is committed to leveraging the talent of a diverse workforce to create great opportunities for our business and our people. EOE/AA. Minority/Female/Sexual Orientation/Gender Identity/Disability/Vet
Oct 08, 2026
Full time
Data Scientist - onsite London - PhD required Job Category: Indiv Contributor-Slry Requisition Number: DATAS003457 Posted : September 9, 2026 Full-Time On-site Locations Showing 1 location London, UK W1W7NY, GBR Description WELLTOWER - REIMAGINE REAL ESTATE WITH US At Welltower, we're transforming how the world thinks about senior living and wellness-focused real estate. As a global leader in residential wellness and healthcare infrastructure, we create vibrant, purpose-driven communities where housing, healthcare, and hospitality converge. Our culture is fast-paced, collaborative, and endlessly ambitious-guided by our mantra: The only easy day was yesterday. We're looking for bold, independent thinkers who thrive on challenge, embrace complexity, and are driven to deliver long-term value. Every team member is empowered to think like an owner, innovate fearlessly, and lead from where they stand. If you're passionate about outcomes and inspired by the opportunity to shape the future of healthcare infrastructure, we want you on our best-in-class team. ABOUT THE ROLE The Data Scientist will work with the current Data Science team in the US/Canada, along with the investment/asset management team in the UK, and integrate information from various sources and analyze it for better understanding about how the business performance can be enhanced, and to analyze output from AI and ML tools that automate certain processes for capital allocation in the UK. The Data Scientist will report to the Lead Data Scientist in the US/Canada and have a dotted line to the Head of Investment in the UK, and will help us discover the information hidden in vast amounts of data, and help us make smarter investment and asset management decisions. The primary focus of this role will be in applying machine learning and predictive analytics techniques, doing statistical analysis, and building high-quality prediction systems integrated with our business model. This role will support and challenge the investment and asset management team in understanding locations across the UK where we have potential deals and where we will manage our existing assets. KEY RESPONSIBILITIES Assist the Business Insights team with Welltower's data and analytics strategy and predictive analytics application for UK asset management and investment teams Work with the investment and asset management team to guide them to the right location/market based on the data science platform Selecting features, building and optimizing classifiers using machine learning techniques Extending company's data with third party sources of information as and when needed and integrate the third-party data into the Welltower data science models Analyzing the output of the predictive analytics model to make meaningful information valuable to UK investment process and challenge the UK investment team's thesis with data backed analysis Enhancing data collection procedures to include information that is relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc analysis and presenting results to the UK team OTHER DUTIES Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, and responsibilities that are required of this employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. TRAVEL Minimal travel should be expected. MINIMUM REQUIREMENTS Experience: Knowledge of data and analytics landscape and with at least 2 years of work experience Strong technical skills to include a deep understanding of (but not limited to): Reporting and Analytical Analysis, Predictive Modeling, and Solution Architect Excellent understanding of machine learning techniques and algorithms, such as Tree Based Models, Neural Networks, etc. Experience with common data science toolkits, such as R, MatLab, Python etc. Excellence in at least one of these is highly desirable Experience with data mining and data visualization tools, such as Alteryx, Tableau, PowerBI etc. Applied statistics skills, such as distributions, correlation, statistical testing, regression, etc. Excellent verbal and written communication skills with business and technology partners. Familiarity with Real Estate, Finance and/or Healthcare industries systems and specialist in business consolidation in diverse source systems. Knowledge of enterprise profitability and business planning and forecasting. Education: PhD or Masters in Mathematics, Statistics, Economics, or Financial Analysis with a focus on Predictive Analytics solution. Background in Computer Science, Information Systems, Engineering, Statistics or related field is required. Employment is contingent upon the successful completion of a background check and verification of employment, education, and other credentials relevant to the position. WHAT WE OFFER Competitive Base Salary + Annual Bonus Generous Paid Time Off and Holidays Employee Stock Purchase Program - purchase shares at a 15% discount Pension Scheme + Profit Sharing Program Tuition Assistance Program Comprehensive and progressive Medical/Dental/Vision options Professional Growth And much more! ABOUT WELLTOWER Welltower Inc. (NYSE: WELL) an S&P 500 company, is the world's preeminent residential wellness and healthcare infrastructure company. Our portfolio of 1,500+ Seniors and Wellness Housing communities is positioned at the intersection of housing, healthcare, and hospitality, creating vibrant communities for mature renters and older adults inthe United States,United Kingdom, andCanada. We also seek to support physicians in our Outpatient Medical buildings with the critical infrastructure needed to deliver quality care. Our real estate portfolio is unmatched, located in highly attractive micro-markets with stunning built environments.Yet, we are an unusual real estate organization as we view ourselves as a product company in a real estate wrapper driven by relationships and unconventional culture. Through our disciplined approach to capital allocation powered by our data science platform and superior operating results driven by the Welltower Business System, we aspire to deliver long-term compounding of per share growth and returns for our existing investors - ourNorth Star. Welltower is committed to leveraging the talent of a diverse workforce to create great opportunities for our business and our people. EOE/AA. Minority/Female/Sexual Orientation/Gender Identity/Disability/Vet
Share Senior Research Engineer, ML Lead, Health Frontiers Google London, UK Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Senior Research Engineer, ML Lead, Health Frontiers Bachelor's degree or equivalent practical experience. 5 years of experience in machine learning research or research engineering, including experience leading technical projects. 3 years of experience training, adapting, or evaluating large-scale foundation models, and building data pipelines for heterogeneous datasets. 3 years of experience with modern machine learning frameworks (e.g., JAX, PyTorch, TensorFlow) and distributed training on accelerators. 3 years of experience designing evaluations, metrics, and controlled ablations for research projects. 3 years of experience designing evaluations, metrics, and controlled ablations for research projects. Preferred qualifications: Master's degree or PhD in Computer Science or related technical field. Experience modeling longitudinal or multimodal real-world data (e.g., audio, wearable sensor data, health records). Experience profiling and debugging distributed training on TPU or GPU clusters (including handling data noise and training dynamics). Domain knowledge for health or fitness, combined with experience in scientific study design and causal inference. Record of influential research, deployed ML systems, open-source contributions, or technical leadership in an advanced ML organization. About the job The Health Intelligence team is focused on developing frontier technologies to help everyone live healthier, happier and longer lives. We build large sensor foundation models to drive scientific discovery for novel health biomarkers. In this role, you will be working with world-scale multimodal datasets consisting of longitudinal sensor data, health agent interactions and clinical health records data. In this role, you will focus on driving comprehensive model optimization, novel model architectures (transformers, state-space-models, etc.) and training methods, transform large-scale time-series data and experimentation systems, study training dynamics, design evaluations, and turn successful research into systems that operate reliably in production. You will develop autoresearch agents that accelerate research workflows and scientific discovery. Where existing datasets cannot answer a question, you will work with expert teams to define new endpoints, commission studies, or collect new data. As a team we work at the forefront of technology and have the space to innovate with it. All of us are personally invested in the fitness and health space we work in and are motivated by a desire to meaningfully improve our users' lives. The Health Platforms and Devices team builds innovative products and services that help our users live longer, healthier lives. We bring together the best of Google technologies and AI, health behavior science, and user-centered design to help users organize the health and wellness data, get insight from it, and take action toward their health goals. We do this with a suite of apps, services, and health wearables. We aim to make consumer health more personal, proactive, and actionable. Responsibilities Design, train, and evaluate machine learning models, owning the full experimentation loop. Develop automated-research agents capable of running quantitative evaluations, generating hypotheses, and executing computational experiments. Develop evaluation frameworks that test scientific reasoning, temporal understanding, calibration, generalization, data leakage, and real-world utility. Work with scientists to translate research questions into measurable endpoints and experimental designs, and provide technical leadership through architecture reviews and mentoring. Provide decisive technical leadership by taking ownership in team settings, actively steering technical agendas, and making concrete decisions to overcome technical stalemates. Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
Oct 08, 2026
Full time
Share Senior Research Engineer, ML Lead, Health Frontiers Google London, UK Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Senior Research Engineer, ML Lead, Health Frontiers Bachelor's degree or equivalent practical experience. 5 years of experience in machine learning research or research engineering, including experience leading technical projects. 3 years of experience training, adapting, or evaluating large-scale foundation models, and building data pipelines for heterogeneous datasets. 3 years of experience with modern machine learning frameworks (e.g., JAX, PyTorch, TensorFlow) and distributed training on accelerators. 3 years of experience designing evaluations, metrics, and controlled ablations for research projects. 3 years of experience designing evaluations, metrics, and controlled ablations for research projects. Preferred qualifications: Master's degree or PhD in Computer Science or related technical field. Experience modeling longitudinal or multimodal real-world data (e.g., audio, wearable sensor data, health records). Experience profiling and debugging distributed training on TPU or GPU clusters (including handling data noise and training dynamics). Domain knowledge for health or fitness, combined with experience in scientific study design and causal inference. Record of influential research, deployed ML systems, open-source contributions, or technical leadership in an advanced ML organization. About the job The Health Intelligence team is focused on developing frontier technologies to help everyone live healthier, happier and longer lives. We build large sensor foundation models to drive scientific discovery for novel health biomarkers. In this role, you will be working with world-scale multimodal datasets consisting of longitudinal sensor data, health agent interactions and clinical health records data. In this role, you will focus on driving comprehensive model optimization, novel model architectures (transformers, state-space-models, etc.) and training methods, transform large-scale time-series data and experimentation systems, study training dynamics, design evaluations, and turn successful research into systems that operate reliably in production. You will develop autoresearch agents that accelerate research workflows and scientific discovery. Where existing datasets cannot answer a question, you will work with expert teams to define new endpoints, commission studies, or collect new data. As a team we work at the forefront of technology and have the space to innovate with it. All of us are personally invested in the fitness and health space we work in and are motivated by a desire to meaningfully improve our users' lives. The Health Platforms and Devices team builds innovative products and services that help our users live longer, healthier lives. We bring together the best of Google technologies and AI, health behavior science, and user-centered design to help users organize the health and wellness data, get insight from it, and take action toward their health goals. We do this with a suite of apps, services, and health wearables. We aim to make consumer health more personal, proactive, and actionable. Responsibilities Design, train, and evaluate machine learning models, owning the full experimentation loop. Develop automated-research agents capable of running quantitative evaluations, generating hypotheses, and executing computational experiments. Develop evaluation frameworks that test scientific reasoning, temporal understanding, calibration, generalization, data leakage, and real-world utility. Work with scientists to translate research questions into measurable endpoints and experimental designs, and provide technical leadership through architecture reviews and mentoring. Provide decisive technical leadership by taking ownership in team settings, actively steering technical agendas, and making concrete decisions to overcome technical stalemates. Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
About the company the company is a global consulting firm that partners with leaders to drive change and create value. With deep industry expertise, and enabled by advanced technology, the firm helps clients to deliver with greater confidence and certainty. With over 2,000 people across the UK, Europe, North America, Asia and Australia, the firm combines global insight with local understanding. The firm works across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms, with capabilities spanning strategy, transformation and operational excellence - all powered by advanced technology, data, AI and digital innovation. Clients value the company's collaborative approach and the way its teams integrate seamlessly - all working with a shared understanding of what matters most. The firm is known for its kind, curious experts who listen closely and care deeply about client success as they help clients transform energy markets, modernise financial platforms, expand telecoms and digital networks through advanced data analytics, enable digital services in government, and unlock growth in consumer sectors. Certified as a Great Place to Work around the world, the company has been recognised by the Financial Times in 22 categories of its UK Leading Management Consultants rankings, and by Forbes for four consecutive years as one of the World's Best Management Consulting Firms. Our Solutions & AI Lab (SAIL) practice are looking for an experienced AI Architect to join the team. Our Solutions & AI Labs practice helps clients control their data, turn it into actionable insight, and better leverage it through AI and Machine Learning solutions embedded directly into business processes. We support clients across a range of industries and offer deepexpertisein AI/ML, Cloud, Platform Engineering and Managed Solutions. We are looking for an experienced Senior Manager to serve as an AI Architect - someone who can design the end-to-end architecture for enterprise AI platforms, lead consultancy engagements, and grow our AI & Solutions Engineering capability. The AI Architect role owns the technical blueprint for AI-enabled solutions delivered in and around our clients' environments, combining deep architectural specialism with the commercial and leadership skills to shape and grow our practice. This is a role for someone who thrives at the intersection of client advisory,AIplatform architecture and hands-on delivery leadership - and who has a genuine passion for bringing AI systems to production at scale. What you will be doing As a Senior Manager and AI Architect, you will own and lead the architecture of complex AI programmes end-to-end - from shaping the opportunity and winning the work, through solution design, deliverygovernanceand team leadership. You will bring SME-level depth in enterprise AI architecture and apply it to create real, lasting value for our clients. Although we do not expect you to be an expert in every technology listed below simultaneously, our team consists of people who can advise clients as well as bring deep technical knowledge when needed. Key responsibilities span the following areas. Engagement & delivery leadership Own and lead the architecture of complex AI and data transformation engagements, taking accountability for solution design, quality, technicalriskand client outcomes. Lead and resource multi-disciplinary delivery teams - architects, engineers, datascientistsand consultants - providing clear direction, technicaloversightand people development. Manage engagement resourcing: forecast team requirements, work with practice leadership to staff engagements, and develop the talent pipeline through mentoring of junior practitioners. Proactivelyidentifyand manage delivery and architectural risks in complex stakeholder environments, escalating appropriately andmaintainingclient confidence throughout. Communicate clearly to both technical teams and senior client stakeholders, translating architectural complexity into actionable insight and decisive recommendation. Conduct rigorous architecture and design reviewsand uphold engineering standards across every engagement you lead. Stakeholder management & advisory Act as a trusted advisor to client architects, CTOs, CDAOs and engineering leads, earning trust through depth of knowledge and a demonstrable deliverytrack record. Build andmaintainstrong, senior client relationships, navigating competing priorities across business,technologyand risk functions. Facilitate architecture workshops and decision forums, driving alignment across diverse stakeholder groups and securing buy-in for target-state designs. Translate business strategy into architectural roadmaps, sequencinginvestmentand change in a way that balances ambition with deliverability. Business development & bid support Play a leading role in business development:identifyingnew opportunities, shaping propositions, and supporting or leading bids and tender responses for AI and technology engagements. Contribute to proposal writing, articulating our capabilities and differentiators, including authoring technical and architecture sections of bid responses to client tenders and RFPs. Support practice-level growth initiatives, including account planning, capability development, and go-to-market positioning for AI architecture and solutions engineering services. Technical architecture - what you will design You will be the design authority for enterprise AI platforms, able to reason across the full stack and make credible technology selections. We expect expert-level depth in several of the areas below and working knowledge across the rest. AI platform & cloud architecture Architect AI andDataPlatforms using a mix of technologies including Databricks, Snowflake,Claude Enterpriseand the native services of Azure,AWSand GCP-selecting the right tool for the workload rather than defaulting to a single vendor. Design for scalability, security, costefficiencyand multi-cloud / hybrid patterns, with a strong grasp of containerisation, infrastructure-as-code, event-drivenarchitecturesand CI/CD. Balance technical excellence with delivery pragmatism and commercial realities, championing the path from prototype to production. Enterprise AI ecosystem integration Bring awareness of the broader enterprise landscape and how AI integrates with core operational systems such as SAP, Salesforce, ServiceNow and other systems of record and engagement. Design integration patterns that let AI capabilities interoperate safely with enterprise data, identity,workflowand process automation platforms- including MCP and A2A and how these capabilities enable an enterprise Agent mesh. Understand the data,governanceand change implications of embedding AI into mission-critical enterprise processes. Orchestration & control plane Architect the orchestration and control-plane layer that governs how AI capabilities are exposed,routedand managed across the enterprise. Design MCP, AI and LLM gateway layers for secure,observableand policy-controlled access to models and tools. Design agent and skills registries - including recommending suitable technologies and patterns - to enable discovery,reuseand governance of agentic capabilities. Define the control plane for routing, rate limiting, cost management, modelselectionand version control across multiple model providers. AI solution design Design retrieval and reasoning architectures including RAG, corrective RAG (CRAG), and agentic patterns, selecting the right approach for a given business problem. Architect agent harnesses and their components - planning, memory, tool use, statemanagementand multi-agent coordination. Design prompt strategies, contextmanagementand grounding approaches for reliable, production-grade LLM behaviour. Evaluation, guardrails & responsible AI Design evaluation frameworks and guardrails that make AI systems safe,reliableand measurable - covering accuracy, safety, bias, and task success. Embed responsible-AI and governance controls aligned toemergingregulation and client risk appetites. Define human-in-the-loop and fallback strategies for high-stakes use cases. Observability & operations Architect logging, monitoring,tracingand cost-observability across the AI stack, including model,agentand platform telemetry. Design for drift detection, performancemonitoringand continuous evaluation in production (LLMOps/MLOps). Establish operational patterns for reliability, incidentresponseand lifecycle management of AI systems at scale. Your skills and experience We're seekinga technically credible, commercially aware leader who brings a rare combination of architectural depth, deliveryaccountabilityand client advisory skill - someone energised by the complexity of taking AI solutions to production at scale. 7+ yearsin technology consulting,architectureor AI/ML engineering, with at least 3 years in a senior leadership or lead-architect role - including accountability for end-to-end solution design,resourcingand commercial outcomes. . click apply for full job details
Oct 08, 2026
Full time
About the company the company is a global consulting firm that partners with leaders to drive change and create value. With deep industry expertise, and enabled by advanced technology, the firm helps clients to deliver with greater confidence and certainty. With over 2,000 people across the UK, Europe, North America, Asia and Australia, the firm combines global insight with local understanding. The firm works across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms, with capabilities spanning strategy, transformation and operational excellence - all powered by advanced technology, data, AI and digital innovation. Clients value the company's collaborative approach and the way its teams integrate seamlessly - all working with a shared understanding of what matters most. The firm is known for its kind, curious experts who listen closely and care deeply about client success as they help clients transform energy markets, modernise financial platforms, expand telecoms and digital networks through advanced data analytics, enable digital services in government, and unlock growth in consumer sectors. Certified as a Great Place to Work around the world, the company has been recognised by the Financial Times in 22 categories of its UK Leading Management Consultants rankings, and by Forbes for four consecutive years as one of the World's Best Management Consulting Firms. Our Solutions & AI Lab (SAIL) practice are looking for an experienced AI Architect to join the team. Our Solutions & AI Labs practice helps clients control their data, turn it into actionable insight, and better leverage it through AI and Machine Learning solutions embedded directly into business processes. We support clients across a range of industries and offer deepexpertisein AI/ML, Cloud, Platform Engineering and Managed Solutions. We are looking for an experienced Senior Manager to serve as an AI Architect - someone who can design the end-to-end architecture for enterprise AI platforms, lead consultancy engagements, and grow our AI & Solutions Engineering capability. The AI Architect role owns the technical blueprint for AI-enabled solutions delivered in and around our clients' environments, combining deep architectural specialism with the commercial and leadership skills to shape and grow our practice. This is a role for someone who thrives at the intersection of client advisory,AIplatform architecture and hands-on delivery leadership - and who has a genuine passion for bringing AI systems to production at scale. What you will be doing As a Senior Manager and AI Architect, you will own and lead the architecture of complex AI programmes end-to-end - from shaping the opportunity and winning the work, through solution design, deliverygovernanceand team leadership. You will bring SME-level depth in enterprise AI architecture and apply it to create real, lasting value for our clients. Although we do not expect you to be an expert in every technology listed below simultaneously, our team consists of people who can advise clients as well as bring deep technical knowledge when needed. Key responsibilities span the following areas. Engagement & delivery leadership Own and lead the architecture of complex AI and data transformation engagements, taking accountability for solution design, quality, technicalriskand client outcomes. Lead and resource multi-disciplinary delivery teams - architects, engineers, datascientistsand consultants - providing clear direction, technicaloversightand people development. Manage engagement resourcing: forecast team requirements, work with practice leadership to staff engagements, and develop the talent pipeline through mentoring of junior practitioners. Proactivelyidentifyand manage delivery and architectural risks in complex stakeholder environments, escalating appropriately andmaintainingclient confidence throughout. Communicate clearly to both technical teams and senior client stakeholders, translating architectural complexity into actionable insight and decisive recommendation. Conduct rigorous architecture and design reviewsand uphold engineering standards across every engagement you lead. Stakeholder management & advisory Act as a trusted advisor to client architects, CTOs, CDAOs and engineering leads, earning trust through depth of knowledge and a demonstrable deliverytrack record. Build andmaintainstrong, senior client relationships, navigating competing priorities across business,technologyand risk functions. Facilitate architecture workshops and decision forums, driving alignment across diverse stakeholder groups and securing buy-in for target-state designs. Translate business strategy into architectural roadmaps, sequencinginvestmentand change in a way that balances ambition with deliverability. Business development & bid support Play a leading role in business development:identifyingnew opportunities, shaping propositions, and supporting or leading bids and tender responses for AI and technology engagements. Contribute to proposal writing, articulating our capabilities and differentiators, including authoring technical and architecture sections of bid responses to client tenders and RFPs. Support practice-level growth initiatives, including account planning, capability development, and go-to-market positioning for AI architecture and solutions engineering services. Technical architecture - what you will design You will be the design authority for enterprise AI platforms, able to reason across the full stack and make credible technology selections. We expect expert-level depth in several of the areas below and working knowledge across the rest. AI platform & cloud architecture Architect AI andDataPlatforms using a mix of technologies including Databricks, Snowflake,Claude Enterpriseand the native services of Azure,AWSand GCP-selecting the right tool for the workload rather than defaulting to a single vendor. Design for scalability, security, costefficiencyand multi-cloud / hybrid patterns, with a strong grasp of containerisation, infrastructure-as-code, event-drivenarchitecturesand CI/CD. Balance technical excellence with delivery pragmatism and commercial realities, championing the path from prototype to production. Enterprise AI ecosystem integration Bring awareness of the broader enterprise landscape and how AI integrates with core operational systems such as SAP, Salesforce, ServiceNow and other systems of record and engagement. Design integration patterns that let AI capabilities interoperate safely with enterprise data, identity,workflowand process automation platforms- including MCP and A2A and how these capabilities enable an enterprise Agent mesh. Understand the data,governanceand change implications of embedding AI into mission-critical enterprise processes. Orchestration & control plane Architect the orchestration and control-plane layer that governs how AI capabilities are exposed,routedand managed across the enterprise. Design MCP, AI and LLM gateway layers for secure,observableand policy-controlled access to models and tools. Design agent and skills registries - including recommending suitable technologies and patterns - to enable discovery,reuseand governance of agentic capabilities. Define the control plane for routing, rate limiting, cost management, modelselectionand version control across multiple model providers. AI solution design Design retrieval and reasoning architectures including RAG, corrective RAG (CRAG), and agentic patterns, selecting the right approach for a given business problem. Architect agent harnesses and their components - planning, memory, tool use, statemanagementand multi-agent coordination. Design prompt strategies, contextmanagementand grounding approaches for reliable, production-grade LLM behaviour. Evaluation, guardrails & responsible AI Design evaluation frameworks and guardrails that make AI systems safe,reliableand measurable - covering accuracy, safety, bias, and task success. Embed responsible-AI and governance controls aligned toemergingregulation and client risk appetites. Define human-in-the-loop and fallback strategies for high-stakes use cases. Observability & operations Architect logging, monitoring,tracingand cost-observability across the AI stack, including model,agentand platform telemetry. Design for drift detection, performancemonitoringand continuous evaluation in production (LLMOps/MLOps). Establish operational patterns for reliability, incidentresponseand lifecycle management of AI systems at scale. Your skills and experience We're seekinga technically credible, commercially aware leader who brings a rare combination of architectural depth, deliveryaccountabilityand client advisory skill - someone energised by the complexity of taking AI solutions to production at scale. 7+ yearsin technology consulting,architectureor AI/ML engineering, with at least 3 years in a senior leadership or lead-architect role - including accountability for end-to-end solution design,resourcingand commercial outcomes. . click apply for full job details
Software Dev Engineer, Amazon Security Automation Job ID: Amazon UK Services Ltd. At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. The NextGen Security Automation team is looking for a skilled and driven Software Development Engineer (SDE II) to build autonomous security solutions that protect Amazon's customers. As an SDE II, you will leverage AI/ML technologies to automate detection, analysis, and response across proactive, offensive, and defensive security at scale. Your work will directly enhance Amazon's security posture by improving detection capabilities, strengthening guardrails, and advancing automated security tools. Key job responsibilities Design and develop AI/ML-driven security automation systems to detect and mitigate threats at scale. Build and maintain scalable applications that enable real-time threat detection and response. Collaborate with security teams to enhance existing security practices, guardrails, and tooling. Develop automated detection systems integrated into Amazon's security infrastructure. Research and prototype new security solutions, evaluating design approaches for technical feasibility. A day in the life Your day kicks off sipping your morning coffee while diving into the future of autonomous security at Amazon. You're not just coding - you're architecting intelligent systems that drive proactive, offensive, and defensive security at Amazon scale. Working alongside top security engineers and scientists, you're building automated systems that will protect millions of customers across one of the world's largest tech ecosystems. Every line of code you write helps safeguard Amazon's vast digital landscape. It's a fast-paced environment where you'll work with advanced technology to build security solutions that protect millions of Amazon customers. About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why Amazon Security At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve. Inclusive Team Culture In Amazon Security, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training and Career growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. The NextGen Security Automation team builds AI-driven security solutions that protect millions of Amazon customers while ensuring strong data governance. We thrive on innovation, collaboration, and solving complex security challenges at scale. DEI is central to our work - we believe diverse perspectives drive stronger solutions. With a focus on automation and intelligence, we push boundaries to keep Amazon's customers and their data secure. Basic Qualifications Experience (non-internship) in professional software development Experience in professional, non-internship software development Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design Minimum 6+ years of experience building complex software systems that have been successfully delivered to customers Preferred Qualifications Bachelor's degree in computer science or equivalent Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 Experience developing, deploying and managing AI products at scale Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Oct 08, 2026
Full time
Software Dev Engineer, Amazon Security Automation Job ID: Amazon UK Services Ltd. At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. The NextGen Security Automation team is looking for a skilled and driven Software Development Engineer (SDE II) to build autonomous security solutions that protect Amazon's customers. As an SDE II, you will leverage AI/ML technologies to automate detection, analysis, and response across proactive, offensive, and defensive security at scale. Your work will directly enhance Amazon's security posture by improving detection capabilities, strengthening guardrails, and advancing automated security tools. Key job responsibilities Design and develop AI/ML-driven security automation systems to detect and mitigate threats at scale. Build and maintain scalable applications that enable real-time threat detection and response. Collaborate with security teams to enhance existing security practices, guardrails, and tooling. Develop automated detection systems integrated into Amazon's security infrastructure. Research and prototype new security solutions, evaluating design approaches for technical feasibility. A day in the life Your day kicks off sipping your morning coffee while diving into the future of autonomous security at Amazon. You're not just coding - you're architecting intelligent systems that drive proactive, offensive, and defensive security at Amazon scale. Working alongside top security engineers and scientists, you're building automated systems that will protect millions of customers across one of the world's largest tech ecosystems. Every line of code you write helps safeguard Amazon's vast digital landscape. It's a fast-paced environment where you'll work with advanced technology to build security solutions that protect millions of Amazon customers. About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why Amazon Security At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve. Inclusive Team Culture In Amazon Security, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training and Career growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. The NextGen Security Automation team builds AI-driven security solutions that protect millions of Amazon customers while ensuring strong data governance. We thrive on innovation, collaboration, and solving complex security challenges at scale. DEI is central to our work - we believe diverse perspectives drive stronger solutions. With a focus on automation and intelligence, we push boundaries to keep Amazon's customers and their data secure. Basic Qualifications Experience (non-internship) in professional software development Experience in professional, non-internship software development Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design Minimum 6+ years of experience building complex software systems that have been successfully delivered to customers Preferred Qualifications Bachelor's degree in computer science or equivalent Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 Experience developing, deploying and managing AI products at scale Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Senior Machine Learning Engineer (Maternity Leave Cover) Department: Platform Delivery Employment Type: Fixed Term - Full Time Location: London Description The Machine Learning Engineer role sits within Client Delivery, embedded in the Data & Analytics Consulting (DACs) team - a technical, client-facing group of Data Scientists and ML Engineers responsible for building and operationalising advanced machine learning and AI. The Machine Learning Engineer role sits within Client Delivery, embedded in the Data & Analytics Consulting (DACs) team - a technical, client-facing group of Data Scientists and ML Engineers responsible for building and operationalising advanced machine learning and AI components across Xantura's projects. As an ML Engineer here, your core work is designing, training, evaluating, and productionising machine learning models on complex, multi-source datasets from local authorities. You will engineer high-performance training pipelines, build embedding-based and sequence models, implement LLM and RAG workflows, and develop containerised model services that integrate directly into the OneView platform. This includes hands-on work with model architectures, feature engineering, model optimisation, performance debugging, schema-aligned data preparation, and ML-driven interfaces. This is a role for engineers who want to build real models, ship real systems, and solve real operational ML problems - not just prototypes. You will work directly with production data, client technical teams, and our internal engineering ecosystem to deliver AI components that are robust, scalable, and deployed into live environments. Key Responsibilities Machine learning engineering Design, train and optimise predictive models using advanced architectures such as gradient boosted trees, temporal models and embedding based models. Build robust training, evaluation and monitoring pipelines to ensure model quality, reproducibility and auditability. Implement feature engineering, hyperparameter tuning, model debugging and performance optimisation. Productionise models so they run reliably and efficiently at scale in client environments. Data engineering Own schema aware data flows for modelling and cohorts; validate, transform and version datasets used in training and inference. Manage and evolve database schemas; optimise SQL, indexing and partitioning for large training and scoring workloads. Technical delivery Lead the modelling and data engineering components of client projects alongside DACs and Business Consultants. Acquire and extract data from client source systems Build and validate cohort logic to ensure accuracy, interpretability and alignment with client needs. Troubleshoot and resolve complex modelling and pipeline issues throughout delivery. AI engineering Build and integrate LLM based components including embedding pipelines, RAG workflows and text analysis models. Develop and deploy agentic and multicomponent AI systems using modern ML frameworks. Engineer high performance NLP and sequence models for information extraction, classification and risk prediction. Engineering level platform configuration Configure advanced OneView components linked to modelling outputs such as risk logic, summaries and scoring pathways. Contribute modelling innovations, performance insights and engineering improvements back into the platform. Knowledge sharing and technical leadership Act as an SME for machine learning, AI and model engineering within DACs. Mentor DACs on Python, modelling best practice, data engineering fundamentals and debugging approaches. Produce documentation, templates and reusable components to raise engineering standards across delivery. What are we looking for? We'd love to hear from you if you have: 3-5+ years' experience in machine learning engineering Strong Python engineering skills and experience with modern ML frameworks Practical experience training and evaluating models (tree based, temporal, embedding/NLP or LLM based) Ability to build reproducible training and evaluation pipelines Experience containerising and deploying models (e.g., Docker, Fast API) Solid data and database engineering Strong SQL and experience working with relational databases Understanding of schemas, data transformations and (ideally) DBT Experience preparing data for model training and scoring Hands on AI/LLM experience Working with embeddings, vector databases or RAG style workflows Experience applying NLP or sequence models to real world datasets Experience delivering technical work to clients or stakeholders Comfortable defining data requirements, discussing modelling decisions and troubleshooting issues in real time Clear communication and collaborative mindset Able to explain technical concepts simply and work closely with data scientists, engineers and consultants Bonus points if you have: Experience with Azure ML, AKS or similar cloud environments Experience with public sector datasets or analytical workflows Location - This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1-2 days per week. Some travel is also required for on-site client engagements as needed. Please note this is a 12 month Maternity leave cover opportunity What can we offer you? Competitive salary reviewed annually Work for a passionate, mission-driven company solving society's big problems Work flexible hours around life commitments with a focus on delivering company value rather than hours worked Ability to work remotely (excluding face-to-face Team Meetings and client meetings) Training and development opportunities 25 days annual leave (plus bank holidays) Company pension Private medical insurance Generous enhanced parental leave policies Cycle to work scheme Flu Vaccinations Eye Test and contribution towards Glasses for VDU use Employee Assistance Programme Mental health and wellbeing support Remote GP access Counselling/therapy Physiotherapy Medical second opinions
Oct 08, 2026
Full time
Senior Machine Learning Engineer (Maternity Leave Cover) Department: Platform Delivery Employment Type: Fixed Term - Full Time Location: London Description The Machine Learning Engineer role sits within Client Delivery, embedded in the Data & Analytics Consulting (DACs) team - a technical, client-facing group of Data Scientists and ML Engineers responsible for building and operationalising advanced machine learning and AI. The Machine Learning Engineer role sits within Client Delivery, embedded in the Data & Analytics Consulting (DACs) team - a technical, client-facing group of Data Scientists and ML Engineers responsible for building and operationalising advanced machine learning and AI components across Xantura's projects. As an ML Engineer here, your core work is designing, training, evaluating, and productionising machine learning models on complex, multi-source datasets from local authorities. You will engineer high-performance training pipelines, build embedding-based and sequence models, implement LLM and RAG workflows, and develop containerised model services that integrate directly into the OneView platform. This includes hands-on work with model architectures, feature engineering, model optimisation, performance debugging, schema-aligned data preparation, and ML-driven interfaces. This is a role for engineers who want to build real models, ship real systems, and solve real operational ML problems - not just prototypes. You will work directly with production data, client technical teams, and our internal engineering ecosystem to deliver AI components that are robust, scalable, and deployed into live environments. Key Responsibilities Machine learning engineering Design, train and optimise predictive models using advanced architectures such as gradient boosted trees, temporal models and embedding based models. Build robust training, evaluation and monitoring pipelines to ensure model quality, reproducibility and auditability. Implement feature engineering, hyperparameter tuning, model debugging and performance optimisation. Productionise models so they run reliably and efficiently at scale in client environments. Data engineering Own schema aware data flows for modelling and cohorts; validate, transform and version datasets used in training and inference. Manage and evolve database schemas; optimise SQL, indexing and partitioning for large training and scoring workloads. Technical delivery Lead the modelling and data engineering components of client projects alongside DACs and Business Consultants. Acquire and extract data from client source systems Build and validate cohort logic to ensure accuracy, interpretability and alignment with client needs. Troubleshoot and resolve complex modelling and pipeline issues throughout delivery. AI engineering Build and integrate LLM based components including embedding pipelines, RAG workflows and text analysis models. Develop and deploy agentic and multicomponent AI systems using modern ML frameworks. Engineer high performance NLP and sequence models for information extraction, classification and risk prediction. Engineering level platform configuration Configure advanced OneView components linked to modelling outputs such as risk logic, summaries and scoring pathways. Contribute modelling innovations, performance insights and engineering improvements back into the platform. Knowledge sharing and technical leadership Act as an SME for machine learning, AI and model engineering within DACs. Mentor DACs on Python, modelling best practice, data engineering fundamentals and debugging approaches. Produce documentation, templates and reusable components to raise engineering standards across delivery. What are we looking for? We'd love to hear from you if you have: 3-5+ years' experience in machine learning engineering Strong Python engineering skills and experience with modern ML frameworks Practical experience training and evaluating models (tree based, temporal, embedding/NLP or LLM based) Ability to build reproducible training and evaluation pipelines Experience containerising and deploying models (e.g., Docker, Fast API) Solid data and database engineering Strong SQL and experience working with relational databases Understanding of schemas, data transformations and (ideally) DBT Experience preparing data for model training and scoring Hands on AI/LLM experience Working with embeddings, vector databases or RAG style workflows Experience applying NLP or sequence models to real world datasets Experience delivering technical work to clients or stakeholders Comfortable defining data requirements, discussing modelling decisions and troubleshooting issues in real time Clear communication and collaborative mindset Able to explain technical concepts simply and work closely with data scientists, engineers and consultants Bonus points if you have: Experience with Azure ML, AKS or similar cloud environments Experience with public sector datasets or analytical workflows Location - This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1-2 days per week. Some travel is also required for on-site client engagements as needed. Please note this is a 12 month Maternity leave cover opportunity What can we offer you? Competitive salary reviewed annually Work for a passionate, mission-driven company solving society's big problems Work flexible hours around life commitments with a focus on delivering company value rather than hours worked Ability to work remotely (excluding face-to-face Team Meetings and client meetings) Training and development opportunities 25 days annual leave (plus bank holidays) Company pension Private medical insurance Generous enhanced parental leave policies Cycle to work scheme Flu Vaccinations Eye Test and contribution towards Glasses for VDU use Employee Assistance Programme Mental health and wellbeing support Remote GP access Counselling/therapy Physiotherapy Medical second opinions
Your mission As part of the Data Science team, the Scientific Data Engineer will divide their time between digitalization and data analysis. The candidate will develop and maintain the R&D department's data model, data pipelines and dashboarding to support R&D activities. These span a wide range of areas including electronic lab notebook templatization and integrations, data capture and storage, results processing, dashboarding, and statistical analysis activities. They will also share responsibility with the wider Data Science team for providing technical support to scientists across these areas. Job Description Major Activities Write well-documented and well-tested ELN templates that follow company best practices. Develop tools to maintain and ensure data integrity throughout the data lifecycle. Develop SQL queries to improve data accessibility for operational and scientific user-groups. Implement dashboards to improve data accessibility across the R&D organisation. Perform data mining, data exploration and feature generation to bring proof of concept AI/ML / statistical / mechanistic / hybrid modelling in collaboration with data scientists and bench scientists. Serve as part of the technical support team for software utilised by R&D staff. Train end-users on adequate use of tools released for general use. Produce rigorous documentation of all software development processes. Maintain up-to-date knowledge on state-of-the-art data analysis practices applicable to life sciences R&D. Key Performance Indicators Accurately and effectively translate user requirements into successful ELN templates and data pipelines. Timely prioritisation and resolution of user- reported bugs / requested enhancements. Working on multiple unrelated projects concurrently while adhering to agreed timelines. Key Job Competencies Problem Solving - Identifies and resolves problems in a timely manner; gathers and analyzes information skilfully; develops alternative solutions; works well in group problem solving situations; uses reason even when dealing with emotional topics. Motivation - sets and achieves challenging goals; demonstrates persistence and overcomes obstacles; measures self against standard of excellence. Planning/Organizing - prioritizes and plans work activities; uses time efficiently; plans for additional resources; sets goals and objectives; organizes or schedules other people and their tasks; develops realistic action plans. Professionalism - works well under pressure; treats others with respect and consideration regardless of their status or position; accepts responsibility for own actions; follows through on commitments. Innovation - displays original thinking and creativity; meets challenges with resourcefulness; generates suggestions for improving work; develops innovative approaches and ideas. Oral Communication - speak clearly and persuasively in positive or negative situations; listens and gets clarification; responds well to questions; demonstrates good presentation skills; participates effectively in meetings. Written Communication - writes clearly and informatively; edits work for spelling and grammar; varies writing style to meet needs; presents numerical data effectively. Job Responsibilities No direct reports. Job Background Essential BS/MS degree in Data Science/Data Analysis/Bioprocess Engineering or related discipline Understanding of bioprocessing and/or experience working with bioprocess development data Advanced knowledge of Python and SQL. Desired Previous industrial experience in pharma ELN maintenance (can include internships/placements). Software / Database / Bioprocess model development experience. Knowledge of dashboarding tools such as Tableau, Spotfire and PowerBI.
Oct 08, 2026
Full time
Your mission As part of the Data Science team, the Scientific Data Engineer will divide their time between digitalization and data analysis. The candidate will develop and maintain the R&D department's data model, data pipelines and dashboarding to support R&D activities. These span a wide range of areas including electronic lab notebook templatization and integrations, data capture and storage, results processing, dashboarding, and statistical analysis activities. They will also share responsibility with the wider Data Science team for providing technical support to scientists across these areas. Job Description Major Activities Write well-documented and well-tested ELN templates that follow company best practices. Develop tools to maintain and ensure data integrity throughout the data lifecycle. Develop SQL queries to improve data accessibility for operational and scientific user-groups. Implement dashboards to improve data accessibility across the R&D organisation. Perform data mining, data exploration and feature generation to bring proof of concept AI/ML / statistical / mechanistic / hybrid modelling in collaboration with data scientists and bench scientists. Serve as part of the technical support team for software utilised by R&D staff. Train end-users on adequate use of tools released for general use. Produce rigorous documentation of all software development processes. Maintain up-to-date knowledge on state-of-the-art data analysis practices applicable to life sciences R&D. Key Performance Indicators Accurately and effectively translate user requirements into successful ELN templates and data pipelines. Timely prioritisation and resolution of user- reported bugs / requested enhancements. Working on multiple unrelated projects concurrently while adhering to agreed timelines. Key Job Competencies Problem Solving - Identifies and resolves problems in a timely manner; gathers and analyzes information skilfully; develops alternative solutions; works well in group problem solving situations; uses reason even when dealing with emotional topics. Motivation - sets and achieves challenging goals; demonstrates persistence and overcomes obstacles; measures self against standard of excellence. Planning/Organizing - prioritizes and plans work activities; uses time efficiently; plans for additional resources; sets goals and objectives; organizes or schedules other people and their tasks; develops realistic action plans. Professionalism - works well under pressure; treats others with respect and consideration regardless of their status or position; accepts responsibility for own actions; follows through on commitments. Innovation - displays original thinking and creativity; meets challenges with resourcefulness; generates suggestions for improving work; develops innovative approaches and ideas. Oral Communication - speak clearly and persuasively in positive or negative situations; listens and gets clarification; responds well to questions; demonstrates good presentation skills; participates effectively in meetings. Written Communication - writes clearly and informatively; edits work for spelling and grammar; varies writing style to meet needs; presents numerical data effectively. Job Responsibilities No direct reports. Job Background Essential BS/MS degree in Data Science/Data Analysis/Bioprocess Engineering or related discipline Understanding of bioprocessing and/or experience working with bioprocess development data Advanced knowledge of Python and SQL. Desired Previous industrial experience in pharma ELN maintenance (can include internships/placements). Software / Database / Bioprocess model development experience. Knowledge of dashboarding tools such as Tableau, Spotfire and PowerBI.
About us GoCardless is a global bank payment company. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect and send payments through direct debit, real-time payments and open banking. GoCardless processes US$130bn+ of payments annually, across 30+ countries; helping customers collect and send both recurring and one-off payments, without the chasing, stress or expensive fees. We use AI-powered solutions to improve payment success and reduce fraud. And, with open banking connectivity to over 2,500 banks, we help our customers make faster, more informed decisions. We are headquartered in the UK with offices in London and Leeds, and additional locations in Australia, France, Ireland, Latvia, Portugal and the United States. At GoCardless, we're all about supporting you! We're committed to making our hiring process inclusive and accessible. If you need extra support or adjustments, reach out to your Talent Partner - we're here to help! And remember: we don't expect you to meet every single requirement. If you're excited by this role, we encourage you to apply! The role Fraud prevention is an ever-evolving puzzle, making it one of the most rewarding and impactful areas in fintech. At GoCardless, our Fraud Prevention team develops the intelligent systems that protect our platform, our merchants, and their customers. As a Senior Data Scientist, you will guide the design and delivery of models that operate in real time across our global payment network. You'll work at the intersection of machine learning, graph-based detection, and behavioural modelling to stay ahead of changing patterns turning research into production systems that make a tangible difference in the fight against financial crime. You'll collaborate closely with Engineers, Fraud Analysts, and Product Managers to help shape the technical roadmap as we expand into new markets. Our stack is centred around Google Cloud Platform and Vertex AI, using Python, SQL, and BigQuery to build and support high-performance models at scale. What you'll do Contribute to the full model lifecycle, from initial discovery and feature engineering through to production, experimentation, and continuous monitoring. Design and refine real-time ML systems that reduce false positives and ensure a smooth, secure experience for legitimate customers. Foster a responsive feedback loop, adapting models as patterns evolve to ensure our defences remain robust and effective. Help shape the technical direction of fraud prevention ML at GoCardless, exploring new approaches as we grow globally. Support the team's growth through technical mentorship, knowledge sharing, and a commitment to high-quality code. What excites you Solving complex, dynamic problems: Developing systems that can adapt and respond to changing environments. End-to-end ownership: Seeing a project through from a conceptual business need to a live, impactful solution. Strategic influence: Contributing to the ML roadmap and helping determine what we build next, rather than just how we build it. Holistic Data Science: Engaging in deep-dive analysis, prototyping, and live experimentation. Modern Infrastructure: Building production-grade models on GCP and Vertex AI, with the flexibility to explore advanced architectures. What excites us You hold a degree (or PhD) in a STEM discipline, or bring equivalent depth through commercial experience. You have hands on experience with modelling approaches such as deep learning, graph-based methods, or sequence models. While fintech experience is great, we value transferable skills from fields like cybersecurity or risk modelling. You have a track record of deploying models in production that create measurable value. You can translate complex ML concepts into clear, practical solutions for stakeholders across the business. You enjoy writing clean code and helping the team thrive through thoughtful reviews and shared learning. Base salary range: £99,200 - £148,800 Base salary ranges are based on role, job level, location, and market data. Please note that whilst we strive to offer competitive compensation, our approach is to pay between the minimum and the mid-point of the pay range until performance can be assessed in role. Offers will take into account level of experience, interview assessment, budgets and parity between you and fellow employees at GoCardless doing similar work. (some of) The good stuff Wellbeing - stay healthy with dedicated support and medical cover Work away scheme - gives you the option to work away from your country of residence for up to 90 days in any 12 month period Adaptive Working - allows you to work flexibly, around your lifestyle Parental leave - to suit everyone embarking on life's great adventure Learning Budget - lead your own development with an annual learning budget Time off - generous holiday allowance, + 3 annual volunteer days, + 4 annual business-wide wellness days ('GC Fridays') Life at GoCardless We're an organisation defined by our values; We start with why before we begin any project, to ensure it's aligned with our mission. We act with integrity, always. We care deeply about what we do and we know it's essential that we be humble whilst we do it. Working this way creates the GC magic- the reason we all love showing up to work. Diversity & Inclusion As of April 2025, we had 806 employees (GeeCees) globally, with 524 based in the UK, 163 based in Latvia and 119 across our other offices. To ensure that we're representative of the world around us - and to be able to review relevant benchmarks - we ask GeeCees to voluntarily disclose diversity data. This year, the proportion of GeeCees providing data increased to 88% (up from 79% in 2024). With regards to diversity within GoCardless, we can see GeeCees identifying as: Asian, Black, Mixed or Other - 25% Neurodiverse - 9% LGBTQIA+ - 9% Disabled - 1% Average age - 33 Female - 45% Male - 55% We're rooting for you during your application and GoCardless aims to provide reasonable adjustments to make our recruitment process as remarkable and accessible as we can. Please speak to your Talent Partner if you need extra support. If you want to read about our Employee Resource Groups and objectives here. Sustainability We're committed to reducing our impact on the environment, leaving a more sustainable world for future generations. Check out our sustainability action plan here. Find out more about Life at GoCardless via Twitter, Instagram and LinkedIn.
Oct 08, 2026
Full time
About us GoCardless is a global bank payment company. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect and send payments through direct debit, real-time payments and open banking. GoCardless processes US$130bn+ of payments annually, across 30+ countries; helping customers collect and send both recurring and one-off payments, without the chasing, stress or expensive fees. We use AI-powered solutions to improve payment success and reduce fraud. And, with open banking connectivity to over 2,500 banks, we help our customers make faster, more informed decisions. We are headquartered in the UK with offices in London and Leeds, and additional locations in Australia, France, Ireland, Latvia, Portugal and the United States. At GoCardless, we're all about supporting you! We're committed to making our hiring process inclusive and accessible. If you need extra support or adjustments, reach out to your Talent Partner - we're here to help! And remember: we don't expect you to meet every single requirement. If you're excited by this role, we encourage you to apply! The role Fraud prevention is an ever-evolving puzzle, making it one of the most rewarding and impactful areas in fintech. At GoCardless, our Fraud Prevention team develops the intelligent systems that protect our platform, our merchants, and their customers. As a Senior Data Scientist, you will guide the design and delivery of models that operate in real time across our global payment network. You'll work at the intersection of machine learning, graph-based detection, and behavioural modelling to stay ahead of changing patterns turning research into production systems that make a tangible difference in the fight against financial crime. You'll collaborate closely with Engineers, Fraud Analysts, and Product Managers to help shape the technical roadmap as we expand into new markets. Our stack is centred around Google Cloud Platform and Vertex AI, using Python, SQL, and BigQuery to build and support high-performance models at scale. What you'll do Contribute to the full model lifecycle, from initial discovery and feature engineering through to production, experimentation, and continuous monitoring. Design and refine real-time ML systems that reduce false positives and ensure a smooth, secure experience for legitimate customers. Foster a responsive feedback loop, adapting models as patterns evolve to ensure our defences remain robust and effective. Help shape the technical direction of fraud prevention ML at GoCardless, exploring new approaches as we grow globally. Support the team's growth through technical mentorship, knowledge sharing, and a commitment to high-quality code. What excites you Solving complex, dynamic problems: Developing systems that can adapt and respond to changing environments. End-to-end ownership: Seeing a project through from a conceptual business need to a live, impactful solution. Strategic influence: Contributing to the ML roadmap and helping determine what we build next, rather than just how we build it. Holistic Data Science: Engaging in deep-dive analysis, prototyping, and live experimentation. Modern Infrastructure: Building production-grade models on GCP and Vertex AI, with the flexibility to explore advanced architectures. What excites us You hold a degree (or PhD) in a STEM discipline, or bring equivalent depth through commercial experience. You have hands on experience with modelling approaches such as deep learning, graph-based methods, or sequence models. While fintech experience is great, we value transferable skills from fields like cybersecurity or risk modelling. You have a track record of deploying models in production that create measurable value. You can translate complex ML concepts into clear, practical solutions for stakeholders across the business. You enjoy writing clean code and helping the team thrive through thoughtful reviews and shared learning. Base salary range: £99,200 - £148,800 Base salary ranges are based on role, job level, location, and market data. Please note that whilst we strive to offer competitive compensation, our approach is to pay between the minimum and the mid-point of the pay range until performance can be assessed in role. Offers will take into account level of experience, interview assessment, budgets and parity between you and fellow employees at GoCardless doing similar work. (some of) The good stuff Wellbeing - stay healthy with dedicated support and medical cover Work away scheme - gives you the option to work away from your country of residence for up to 90 days in any 12 month period Adaptive Working - allows you to work flexibly, around your lifestyle Parental leave - to suit everyone embarking on life's great adventure Learning Budget - lead your own development with an annual learning budget Time off - generous holiday allowance, + 3 annual volunteer days, + 4 annual business-wide wellness days ('GC Fridays') Life at GoCardless We're an organisation defined by our values; We start with why before we begin any project, to ensure it's aligned with our mission. We act with integrity, always. We care deeply about what we do and we know it's essential that we be humble whilst we do it. Working this way creates the GC magic- the reason we all love showing up to work. Diversity & Inclusion As of April 2025, we had 806 employees (GeeCees) globally, with 524 based in the UK, 163 based in Latvia and 119 across our other offices. To ensure that we're representative of the world around us - and to be able to review relevant benchmarks - we ask GeeCees to voluntarily disclose diversity data. This year, the proportion of GeeCees providing data increased to 88% (up from 79% in 2024). With regards to diversity within GoCardless, we can see GeeCees identifying as: Asian, Black, Mixed or Other - 25% Neurodiverse - 9% LGBTQIA+ - 9% Disabled - 1% Average age - 33 Female - 45% Male - 55% We're rooting for you during your application and GoCardless aims to provide reasonable adjustments to make our recruitment process as remarkable and accessible as we can. Please speak to your Talent Partner if you need extra support. If you want to read about our Employee Resource Groups and objectives here. Sustainability We're committed to reducing our impact on the environment, leaving a more sustainable world for future generations. Check out our sustainability action plan here. Find out more about Life at GoCardless via Twitter, Instagram and LinkedIn.
Barcelona, Spain; London, United Kingdom; Spain (Remote); United Kingdom (Remote) At Hudl, we build great teams. We hire the best of the best to ensure you're working with people you can constantly learn from. You're trusted to get your work done your way while testing the limits of what's possible and what's next. We work hard to provide a culture where everyone feels supported, and our employees feel it-their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces . We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That's why we help teams from all over the world see their game differently. Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more. Ready to join us? Your Role We're hiring a Senior MLOps Engineer for our Hardware Group to build and scale the machine learning infrastructure that powers Focus, our line of smart cameras. You'll own the edge deployment pipelines that transport neural networks from training clusters to tens of thousands of devices globally, and contribute to the platform that compiles trained models into optimised inference engines for devices like the Jetson Orin, building the "nervous system" for the next generation of automated sports capture. As a Senior MLOps Engineer, you'll: Build scalable Edge infrastructure. You'll design, develop, and maintain the delivery systems that enable us to deploy models to fleets of devices. Own the model compilation platform. You'll build and maintain the pipeline that takes trained models and produces optimised, hardware-specific inference engines - managing TensorRT compilation, precision trade-offs (FP16/INT8), calibration, and engine validation to ensure models run reliably and efficiently on target devices. Work with cross-functional teams. You'll collaborate with Data Scientists, Embedded Engineers, and Product Managers to ensure smooth integration of complex features and capabilities Drive automation and reliability. You'll implement infrastructure to silently test candidate models on production devices and build telemetry pipelines to monitor drift, thermal impact, and inference latency in the wild. Solve complex physical challenges. You'll tackle the unique constraints of the edge - building resilient update mechanisms for low-bandwidth environments, optimising for limited storage, and ensuring devices recover gracefully from network failures. Mentor and lead. You'll share your expertise to establish best practices in Python tooling, Infrastructure-as-Code, and CI/CD, guiding the team toward a more robust, automated future. Location We'd like to hire someone for this role who lives near our offices in London or Barcelona, but we're also open to remote candidates in the UK and Spain. Must-Haves Production MLOps expertise. You've played a key role in building and operating pipelines that deploy models to production, with deep experience in CI/CD, containerization (Docker), and Linux systems. Edge inference & compilation know-how. You have hands on experience compiling and optimising models for embedded hardware - ideally with TensorRT - and understand the practical implications of precision, quantisation, and engine validation at scale. Collaborative. You understand that shipping to hardware is a team sport and can communicate effectively with researchers and low level embedded engineers to translate constraints into solutions. Systems thinking. You can design architectures that handle failure gracefully and understand the implications of deploying to 10,000 heterogeneous devices, including how to manage risk via canary releases and safe rollbacks. Bias towards action. You see your role as solving problems; this means filling gaps and taking initiative as needed to help the team win together. Nice to Haves Experience with our Edge AI stack. Experience with the NVIDIA edge ecosystem (Jetson Orin, DeepStream SDK, TensorRT) is a huge plus. Video Technologies. Familiarity with video pipelines, GStreamer, or ffmpeg. Fleet management. Experience with tools like AWS IoT Greengrass, Balena, or custom OTA / fleet management solutions. Sports Passion. You have an interest in sports technology, video analytics, or performance metrics-but if not, we'll teach you the domain. Our Role Champion work life harmony . We'll give you the flexibility you need in your work life (e.g., flexible vacation time, company wide holidays and timeout (meeting free) days, remote work options and more) so you can enjoy your personal life too. Guarantee autonomy . We have an open, honest culture and we trust our people from day one. Your team will support you, but you'll own your work and have the agency to try new ideas. Encourage career growth . We're lifelong learners who encourage professional development. We'll give you tons of resources and opportunities to keep growing. Provide an environment to help you succeed . We've invested in our offices, designing incredible spaces with our employees in mind. But whether you're at the office or working remotely, we'll provide you the tech stack and hardware to do your best work. Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees-but no matter where you're located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health. Compensation Inclusion at Hudl Hudl is an equal opportunity employer. Through our actions, behaviors and attitude, we'll create an environment where everyone, no matter their differences, feels like they belong. We offer resources to ensure our employees feel safe bringing their authentic selves to work, including employee resource groups and communities . But we recognize there's ongoing work to be done, which is why we track our efforts and commitments in annual inclusion reports . We also know imposter syndrome is real and the confidence gap can get in the way of meeting spectacular candidates.
Oct 08, 2026
Full time
Barcelona, Spain; London, United Kingdom; Spain (Remote); United Kingdom (Remote) At Hudl, we build great teams. We hire the best of the best to ensure you're working with people you can constantly learn from. You're trusted to get your work done your way while testing the limits of what's possible and what's next. We work hard to provide a culture where everyone feels supported, and our employees feel it-their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces . We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That's why we help teams from all over the world see their game differently. Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more. Ready to join us? Your Role We're hiring a Senior MLOps Engineer for our Hardware Group to build and scale the machine learning infrastructure that powers Focus, our line of smart cameras. You'll own the edge deployment pipelines that transport neural networks from training clusters to tens of thousands of devices globally, and contribute to the platform that compiles trained models into optimised inference engines for devices like the Jetson Orin, building the "nervous system" for the next generation of automated sports capture. As a Senior MLOps Engineer, you'll: Build scalable Edge infrastructure. You'll design, develop, and maintain the delivery systems that enable us to deploy models to fleets of devices. Own the model compilation platform. You'll build and maintain the pipeline that takes trained models and produces optimised, hardware-specific inference engines - managing TensorRT compilation, precision trade-offs (FP16/INT8), calibration, and engine validation to ensure models run reliably and efficiently on target devices. Work with cross-functional teams. You'll collaborate with Data Scientists, Embedded Engineers, and Product Managers to ensure smooth integration of complex features and capabilities Drive automation and reliability. You'll implement infrastructure to silently test candidate models on production devices and build telemetry pipelines to monitor drift, thermal impact, and inference latency in the wild. Solve complex physical challenges. You'll tackle the unique constraints of the edge - building resilient update mechanisms for low-bandwidth environments, optimising for limited storage, and ensuring devices recover gracefully from network failures. Mentor and lead. You'll share your expertise to establish best practices in Python tooling, Infrastructure-as-Code, and CI/CD, guiding the team toward a more robust, automated future. Location We'd like to hire someone for this role who lives near our offices in London or Barcelona, but we're also open to remote candidates in the UK and Spain. Must-Haves Production MLOps expertise. You've played a key role in building and operating pipelines that deploy models to production, with deep experience in CI/CD, containerization (Docker), and Linux systems. Edge inference & compilation know-how. You have hands on experience compiling and optimising models for embedded hardware - ideally with TensorRT - and understand the practical implications of precision, quantisation, and engine validation at scale. Collaborative. You understand that shipping to hardware is a team sport and can communicate effectively with researchers and low level embedded engineers to translate constraints into solutions. Systems thinking. You can design architectures that handle failure gracefully and understand the implications of deploying to 10,000 heterogeneous devices, including how to manage risk via canary releases and safe rollbacks. Bias towards action. You see your role as solving problems; this means filling gaps and taking initiative as needed to help the team win together. Nice to Haves Experience with our Edge AI stack. Experience with the NVIDIA edge ecosystem (Jetson Orin, DeepStream SDK, TensorRT) is a huge plus. Video Technologies. Familiarity with video pipelines, GStreamer, or ffmpeg. Fleet management. Experience with tools like AWS IoT Greengrass, Balena, or custom OTA / fleet management solutions. Sports Passion. You have an interest in sports technology, video analytics, or performance metrics-but if not, we'll teach you the domain. Our Role Champion work life harmony . We'll give you the flexibility you need in your work life (e.g., flexible vacation time, company wide holidays and timeout (meeting free) days, remote work options and more) so you can enjoy your personal life too. Guarantee autonomy . We have an open, honest culture and we trust our people from day one. Your team will support you, but you'll own your work and have the agency to try new ideas. Encourage career growth . We're lifelong learners who encourage professional development. We'll give you tons of resources and opportunities to keep growing. Provide an environment to help you succeed . We've invested in our offices, designing incredible spaces with our employees in mind. But whether you're at the office or working remotely, we'll provide you the tech stack and hardware to do your best work. Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees-but no matter where you're located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health. Compensation Inclusion at Hudl Hudl is an equal opportunity employer. Through our actions, behaviors and attitude, we'll create an environment where everyone, no matter their differences, feels like they belong. We offer resources to ensure our employees feel safe bringing their authentic selves to work, including employee resource groups and communities . But we recognize there's ongoing work to be done, which is why we track our efforts and commitments in annual inclusion reports . We also know imposter syndrome is real and the confidence gap can get in the way of meeting spectacular candidates.
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers' success and to our Winning Culture. Our customers rank among the who's who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform. Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebratingour wins - big and small. Supported by operating principles of being strategy-led, values-based and disciplined in execution, you'll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let's build what's next - together! You will join the Predictive Intelligence engineering team within Anaplan, building the backend services that power the ML Engine behind the Syrup platform and Anaplan's forecasting solutions. The team is responsible for the production execution of forecasting and predictive models, the MLOps infrastructure supporting our data scientists, and the data processing services that deliver insights to enterprise customers. This role reports to the Director of Engineering for Predictive Intelligence and works closely with data scientists, ML engineers, and platform partners. Your Impact Design and implement scalable, fault-tolerant predictive intelligence services and features as a core contributor to the ML Engine backend. Lead the technical implementation of MLOps capabilities, including model training pipelines, deployment workflows, and runtime infrastructure for production ML. Partner with data scientists to productionize models and graduate experimental work into stable, observable production services. Drive the evolution of forecasting, scoring, and data processing services with a focus on performance, scalability, and cost efficiency. Take part in on call rotations and own the operational health of high availability production services, including incident response and post incident improvements. Lead design reviews and code reviews, raising the quality bar across the team and mentoring mid level and junior engineers. Identify and drive cross cutting platform improvements that benefit multiple services and teams. Your Qualifications 6+ years of professional software engineering experience building production backend services. Strong proficiency in Python, with a track record of writing performant, well tested production code. Hands on experience operating containerized services on Kubernetes in at least one major cloud (AWS, GCP, or Azure). Experience with data warehousing or analytics technologies such as Snowflake, Iceberg, Trino, or Postgres. Experience designing, deploying, and operating ML models in production, including familiarity with MLOps tooling such as MLflow. Demonstrated ability to work autonomously, take ownership of meaningful systems, and deliver against ambiguous requirements. Track record of being on call for production services and contributing to operational excellence. Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Preferred Skills Experience with gradient boosted tree models, neural networks, and optimization solvers in production. Familiarity with data orchestration tools (e.g., Prefect, Airflow, dbt) and modern data lake architectures. Experience working closely with data scientists to operationalize research code. Multi cloud experience across AWS, GCP, and Azure. Background in forecasting, demand planning, or retail/supply chain domains. Our Commitment to Diversity, Equity, Inclusionand Belonging (DEIB) We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren't just words on paper - this is what drives our innovation, it's how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day! We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Oct 08, 2026
Full time
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers' success and to our Winning Culture. Our customers rank among the who's who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform. Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebratingour wins - big and small. Supported by operating principles of being strategy-led, values-based and disciplined in execution, you'll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let's build what's next - together! You will join the Predictive Intelligence engineering team within Anaplan, building the backend services that power the ML Engine behind the Syrup platform and Anaplan's forecasting solutions. The team is responsible for the production execution of forecasting and predictive models, the MLOps infrastructure supporting our data scientists, and the data processing services that deliver insights to enterprise customers. This role reports to the Director of Engineering for Predictive Intelligence and works closely with data scientists, ML engineers, and platform partners. Your Impact Design and implement scalable, fault-tolerant predictive intelligence services and features as a core contributor to the ML Engine backend. Lead the technical implementation of MLOps capabilities, including model training pipelines, deployment workflows, and runtime infrastructure for production ML. Partner with data scientists to productionize models and graduate experimental work into stable, observable production services. Drive the evolution of forecasting, scoring, and data processing services with a focus on performance, scalability, and cost efficiency. Take part in on call rotations and own the operational health of high availability production services, including incident response and post incident improvements. Lead design reviews and code reviews, raising the quality bar across the team and mentoring mid level and junior engineers. Identify and drive cross cutting platform improvements that benefit multiple services and teams. Your Qualifications 6+ years of professional software engineering experience building production backend services. Strong proficiency in Python, with a track record of writing performant, well tested production code. Hands on experience operating containerized services on Kubernetes in at least one major cloud (AWS, GCP, or Azure). Experience with data warehousing or analytics technologies such as Snowflake, Iceberg, Trino, or Postgres. Experience designing, deploying, and operating ML models in production, including familiarity with MLOps tooling such as MLflow. Demonstrated ability to work autonomously, take ownership of meaningful systems, and deliver against ambiguous requirements. Track record of being on call for production services and contributing to operational excellence. Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Preferred Skills Experience with gradient boosted tree models, neural networks, and optimization solvers in production. Familiarity with data orchestration tools (e.g., Prefect, Airflow, dbt) and modern data lake architectures. Experience working closely with data scientists to operationalize research code. Multi cloud experience across AWS, GCP, and Azure. Background in forecasting, demand planning, or retail/supply chain domains. Our Commitment to Diversity, Equity, Inclusionand Belonging (DEIB) We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren't just words on paper - this is what drives our innovation, it's how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day! We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Anaplan Manchester is seeking an experienced Senior Backend Engineer for our Predictive Intelligence team. You will build the ML Engine backend powering Syrup platform forecasting and analytics, collaborating with data scientists and platform partners to deliver production-grade services. You will lead MLOps pipelines, model deployment, and scalable data processing, while owning on-call rotations and operational excellence. A strong Python background is essential.
Oct 08, 2026
Full time
Anaplan Manchester is seeking an experienced Senior Backend Engineer for our Predictive Intelligence team. You will build the ML Engine backend powering Syrup platform forecasting and analytics, collaborating with data scientists and platform partners to deliver production-grade services. You will lead MLOps pipelines, model deployment, and scalable data processing, while owning on-call rotations and operational excellence. A strong Python background is essential.
Data Scientist London (Hybrid, 3 days per week) Marshall Wolfe are hiring on behalf of our client, a high-growth AI company for a Data Scientist to join their engineering team developing advanced machine learning solutions that help organisations make smarter, data-driven decisions. This role is heavily focused on machine learning, data science and statistics. This is an excellent opportunity for an ambitious, self-starting individual with a strong academic background in Computer Science, Statistics, Mathematics, Machine Learning, or a related subject. You'll join a tight, ambitious team of engineers and report into a highly technical leadership group. This is a hands-on role with real ownership, meaningful impact and exposure to cutting-edge ML and agentic AI development. Key Responsibilities Build, train and optimise machine learning models. Analyse large datasets to identify trends and insights. Develop predictive models for customer behaviour, churn and lifetime value. Apply statistical analysis and experimentation techniques. Collaborate with engineers to deploy and monitor models in production. Requirements Degree in Computer Science, Statistics, Mathematics, Machine Learning or a related quantitative discipline. Hands-on experience using AI coding agents, such as Codex, Claude, or Cursor, to write and improve code, with the ability to understand, review and test output. Strong Python and SQL skills. 2-5 years commercial experience in Data Science, Analytics or Machine Learning is preferred. Solid understanding of machine learning and statistical modelling. Experience with PyTorch, TensorFlow or similar frameworks would be advantageous. Self-motivated, curious and eager to learn. You'll work on real business problems, see your models directly influence customer decisions, and grow quickly in a high-ownership environment. The team is technical, collaborative and values culture fit as much as capability.
Oct 08, 2026
Full time
Data Scientist London (Hybrid, 3 days per week) Marshall Wolfe are hiring on behalf of our client, a high-growth AI company for a Data Scientist to join their engineering team developing advanced machine learning solutions that help organisations make smarter, data-driven decisions. This role is heavily focused on machine learning, data science and statistics. This is an excellent opportunity for an ambitious, self-starting individual with a strong academic background in Computer Science, Statistics, Mathematics, Machine Learning, or a related subject. You'll join a tight, ambitious team of engineers and report into a highly technical leadership group. This is a hands-on role with real ownership, meaningful impact and exposure to cutting-edge ML and agentic AI development. Key Responsibilities Build, train and optimise machine learning models. Analyse large datasets to identify trends and insights. Develop predictive models for customer behaviour, churn and lifetime value. Apply statistical analysis and experimentation techniques. Collaborate with engineers to deploy and monitor models in production. Requirements Degree in Computer Science, Statistics, Mathematics, Machine Learning or a related quantitative discipline. Hands-on experience using AI coding agents, such as Codex, Claude, or Cursor, to write and improve code, with the ability to understand, review and test output. Strong Python and SQL skills. 2-5 years commercial experience in Data Science, Analytics or Machine Learning is preferred. Solid understanding of machine learning and statistical modelling. Experience with PyTorch, TensorFlow or similar frameworks would be advantageous. Self-motivated, curious and eager to learn. You'll work on real business problems, see your models directly influence customer decisions, and grow quickly in a high-ownership environment. The team is technical, collaborative and values culture fit as much as capability.
A career without limits As the nation's flag carrier, we take great pride in connecting Britain with the world and the world with Britain. It's something we've been doing for over 100 years, ever since we launched the world's first international scheduled air service between London and Paris. This originality has been in our blood since day one. It's the spirit we share with the people that fly with us, our partners, and our colleagues. So, whether you are a reassuring voice on the end of a phone, a smile at the door, under a wing keeping the turbines spinning or landing us gently in far-flung places, a job at British Airways is yours to make. We know great things can happen when you're inspired to think big and bring your ambition to work every day, which is why, at British Airways the sky is never the limit. The role: Principal Data Scientist - Finance & Transformation As a senior leader within the Data & AI function, reporting to the Head of Data Delivery, the Principal Data Scientist is accountable for the end-to-end delivery and lifecycle management of high-value data science products or initiatives that support or automate decision-making across critical business areas. Operating within Agile cross-functional squads, they lead teams to scope, design, build, deploy and maintain scalable, production-ready solutions - including predictive models, optimisation engines, and decision-support tools - that integrate seamlessly with business processes and technical infrastructure. The Principal Data Scientist delivers in line with the strategic direction for data science delivery, ensures model compliance and ethical responsibility, and drives continuous improvement in team capabilities and ways of working. They also line manage and coach others to achieve their full potential, fostering a culture of collaboration, innovation and impact. What you'll do: The Principal Data Scientist has accountabilities across the full value chain and coordinates the execution of high-value data science initiatives: Manages and coaches data science teams to deliver a portfolio of data science products from scoping to delivery Scopes and documents ill-defined client needs and frames data science solutions that align with business goals Responsible for the quality and timely delivery of the data science products for an area of the business Reporting on team key performance indicators Acquires, processes and manipulates complex and large raw data to ensure high-quality inputs for models Designs, builds and trains data science products such as business models, predictive analytics tools, recommender systems, natural language processing, anomaly detection, forecasts, optimisation models and decision support systems Works with Digital teams to productionise models and deliver application front ends Translates results in to actionable recommendations Provides guidance to stakeholders on how models created can improve business outcomes Works within cross-functional business and Digital teams Oversees management, improvements to and decommissioning of existing data science products for business area to ensure they are valuable, feasible and usable Monitors industry trends and advancements in data science Ensures adherence to published frameworks in team Ensures model compliance & ethical responsibility in team Ensures best practice is followed in their team Line manages others to achieve full potential Provides ad hoc team cover on an exceptional basis Contributes to conversations on feature prioritisation and roadmap, with an understanding of the trade-off between speed vs. long-term value Communicates feature and modelling approach, trade-offs, and results with the internal team and business stakeholders The Principal Data Scientist is also accountable for ways of working fit for an Agile cross-functional development squad, including: Using Git-versioning best practices for version control Contributing and reviewing pull-requests and product / technical documentation Giving input on prioritization, team process improvements, optimizing technology choices Working independently and giving predictability on delivery timelines What you'll bring to British Airways: Can structure ill-defined business problems and support others Can communicate to large/senior groups Can effectively challenge senior colleagues Can build strong stakeholder relationship networks and set data science strategy Can coach and manage a team Leads scrum methodology and ceremonies Able to independently manage products through the lifecycle & support others Can prioritise own work Can operate in multiple DevOps roles Can lead others on a project Can manage project teams effectively using agile principles and quality assurance Can apply software engineering principles and concepts eg using Git and Python Can build and deploy production ready machine learning pipelines eg using Python Comprehensive cloud understanding Comfortable designing user interface solutions for Machine Learning applications Advanced data wrangling skills applicable to large data eg using SQL, Python Can apply advanced spreadsheet modelling to complex problems eg using Excel Able to apply a range of advanced machine learning and multivariate techniques Proficient in use of Microsoft Office, including advanced Excel and Powerpoint Skills Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights Able to structure business and technical problems, identify trade-offs, and propose solutions Communication of advanced technical concepts to audiences with varying levels of technical skills Managing priorities and timelines to deliver features in a timely manner that meet business requirements Collaborative team-working, giving and receiving feedback, and always seeking to improve team processes Your experience: Numerate degree or equivalent with data science components Experience of leading others in applying data science to business problems Experience in developing industrialised software, especially data science or machine learning software products (required) Experience in relevant business domains (transportation, airlines, operations, network problems) (preferred) What we offer: We believe that all the people who work with us should feel valued for the part they play. It's one of the reasons our rewards go far beyond a competitive salary. From the day you join us, you'll get access to brilliant staff travel benefits including unlimited basic and premium standby tickets on British Airways flights. You'll also receive up to 30 discounted 'Hotline' airfares per year for yourself, friends, and family. At British Airways you'll have the chance to take on new challenges and move forward in a way that feels right for you. We encourage all those who work for us to consider opportunities right across our business to help you develop and progress. We never stand still, and we don't expect our people to either. Inclusion & Diversity At British Airways we all have a part to play in creating an inclusive place to work. Diverse representation among our people is really important to us and we recognise that all our colleagues are uniquely different and bring their own originality, creativity and identity to work. Inclusion and diversity is a key driver of innovation and we're committed to creating a culture where everyone feels that they can be themselves. We're looking for people from all backgrounds and cultures to join us and be a part of our journey to become a Better BA as we continue to connect Britain with the world and the world with Britain.
Oct 08, 2026
Full time
A career without limits As the nation's flag carrier, we take great pride in connecting Britain with the world and the world with Britain. It's something we've been doing for over 100 years, ever since we launched the world's first international scheduled air service between London and Paris. This originality has been in our blood since day one. It's the spirit we share with the people that fly with us, our partners, and our colleagues. So, whether you are a reassuring voice on the end of a phone, a smile at the door, under a wing keeping the turbines spinning or landing us gently in far-flung places, a job at British Airways is yours to make. We know great things can happen when you're inspired to think big and bring your ambition to work every day, which is why, at British Airways the sky is never the limit. The role: Principal Data Scientist - Finance & Transformation As a senior leader within the Data & AI function, reporting to the Head of Data Delivery, the Principal Data Scientist is accountable for the end-to-end delivery and lifecycle management of high-value data science products or initiatives that support or automate decision-making across critical business areas. Operating within Agile cross-functional squads, they lead teams to scope, design, build, deploy and maintain scalable, production-ready solutions - including predictive models, optimisation engines, and decision-support tools - that integrate seamlessly with business processes and technical infrastructure. The Principal Data Scientist delivers in line with the strategic direction for data science delivery, ensures model compliance and ethical responsibility, and drives continuous improvement in team capabilities and ways of working. They also line manage and coach others to achieve their full potential, fostering a culture of collaboration, innovation and impact. What you'll do: The Principal Data Scientist has accountabilities across the full value chain and coordinates the execution of high-value data science initiatives: Manages and coaches data science teams to deliver a portfolio of data science products from scoping to delivery Scopes and documents ill-defined client needs and frames data science solutions that align with business goals Responsible for the quality and timely delivery of the data science products for an area of the business Reporting on team key performance indicators Acquires, processes and manipulates complex and large raw data to ensure high-quality inputs for models Designs, builds and trains data science products such as business models, predictive analytics tools, recommender systems, natural language processing, anomaly detection, forecasts, optimisation models and decision support systems Works with Digital teams to productionise models and deliver application front ends Translates results in to actionable recommendations Provides guidance to stakeholders on how models created can improve business outcomes Works within cross-functional business and Digital teams Oversees management, improvements to and decommissioning of existing data science products for business area to ensure they are valuable, feasible and usable Monitors industry trends and advancements in data science Ensures adherence to published frameworks in team Ensures model compliance & ethical responsibility in team Ensures best practice is followed in their team Line manages others to achieve full potential Provides ad hoc team cover on an exceptional basis Contributes to conversations on feature prioritisation and roadmap, with an understanding of the trade-off between speed vs. long-term value Communicates feature and modelling approach, trade-offs, and results with the internal team and business stakeholders The Principal Data Scientist is also accountable for ways of working fit for an Agile cross-functional development squad, including: Using Git-versioning best practices for version control Contributing and reviewing pull-requests and product / technical documentation Giving input on prioritization, team process improvements, optimizing technology choices Working independently and giving predictability on delivery timelines What you'll bring to British Airways: Can structure ill-defined business problems and support others Can communicate to large/senior groups Can effectively challenge senior colleagues Can build strong stakeholder relationship networks and set data science strategy Can coach and manage a team Leads scrum methodology and ceremonies Able to independently manage products through the lifecycle & support others Can prioritise own work Can operate in multiple DevOps roles Can lead others on a project Can manage project teams effectively using agile principles and quality assurance Can apply software engineering principles and concepts eg using Git and Python Can build and deploy production ready machine learning pipelines eg using Python Comprehensive cloud understanding Comfortable designing user interface solutions for Machine Learning applications Advanced data wrangling skills applicable to large data eg using SQL, Python Can apply advanced spreadsheet modelling to complex problems eg using Excel Able to apply a range of advanced machine learning and multivariate techniques Proficient in use of Microsoft Office, including advanced Excel and Powerpoint Skills Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights Able to structure business and technical problems, identify trade-offs, and propose solutions Communication of advanced technical concepts to audiences with varying levels of technical skills Managing priorities and timelines to deliver features in a timely manner that meet business requirements Collaborative team-working, giving and receiving feedback, and always seeking to improve team processes Your experience: Numerate degree or equivalent with data science components Experience of leading others in applying data science to business problems Experience in developing industrialised software, especially data science or machine learning software products (required) Experience in relevant business domains (transportation, airlines, operations, network problems) (preferred) What we offer: We believe that all the people who work with us should feel valued for the part they play. It's one of the reasons our rewards go far beyond a competitive salary. From the day you join us, you'll get access to brilliant staff travel benefits including unlimited basic and premium standby tickets on British Airways flights. You'll also receive up to 30 discounted 'Hotline' airfares per year for yourself, friends, and family. At British Airways you'll have the chance to take on new challenges and move forward in a way that feels right for you. We encourage all those who work for us to consider opportunities right across our business to help you develop and progress. We never stand still, and we don't expect our people to either. Inclusion & Diversity At British Airways we all have a part to play in creating an inclusive place to work. Diverse representation among our people is really important to us and we recognise that all our colleagues are uniquely different and bring their own originality, creativity and identity to work. Inclusion and diversity is a key driver of innovation and we're committed to creating a culture where everyone feels that they can be themselves. We're looking for people from all backgrounds and cultures to join us and be a part of our journey to become a Better BA as we continue to connect Britain with the world and the world with Britain.
Hybrid - Minimum 3 days on site in London, Tower Bridge HQ About Hometrack At Hometrack, we're redefining the mortgage journey for lenders, brokers and borrowers. We deliver market-leading valuation and risk evaluation services across the property technology and financial technology industries. Our customers include 9 of the top 10 mortgage providers, as well as many others in financial services. Founded in 1999, we made our name with our Automated Valuation Model (AVM) and now provide more than 50 million automated valuations every year. We want to make Houseful more welcoming, fair and representative every day. We'll consider everyone who applies for this role in the same way, regardless of your ethnicity, colour, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, neurodiversity status, family or parental status, or how long you've spent unemployed. You will be responsible for maintaining and improving the industry leading Hometrack AVM (Automated Valuation Model to estimate the value of residential properties). We are always looking to innovate and better identify and understand what data makes a difference to property value and risk and how to incorporate this into our models and products. You'll be at home if you enjoy: Being responsible for the performance of our live models. Detecting model drift and deploying model improvements to ensure the reliability of our valuations for lender clients. Researching new datasets and advanced machine learning techniques that can be used to increase the accuracy of our property valuation model and improve our AI capabilities across our model and product range. Work collaboratively with fellow data scientists, ML Engineers, analysts, product managers and data engineers. Meeting with stakeholders to translate business needs into data science problems. You'll hit the ground running if you have: An advanced degree in Computer Science, Mathematics, Physics, or other quantitative discipline Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code. You worked in an R&D environment and/or you are intimately familiar with the fundamentals of the scientific research method: critical thinking, formulating hypotheses, running experiments, drawing conclusions etc. Experienced at identifying problems that can be solved with machine learning and delivering them from prototype through to production. Great communicator - convey complex ideas and solutions in clear, precise and accessible ways. Team player who cares about accelerating not only Hometrack's technical capabilities, but also empowering colleagues Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps. Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Comfortable working with Docker and containerised applications Experience using AWS or similar cloud computing platform Experience delivering machine learning solutions within regulated environments, including familiarity with Model Risk Management (MRM), governance, or model explainability. There's always room to grow and learn with our roles so please don't be put off if you don't have all of these skills and experiences. It's more important that you're passionate about our mission to improve the home moving and owning experience for everyone. Benefits Everyday Flex - greater flexibility over where and when you work 25 days annual leave + extra days for years of service Day off for volunteering & Digital detox day Festive Closure - business closed for period between Christmas and New Year Cycle to work and electric car schemes Free Calm App membership Enhanced Parental leave Fertility Treatment Financial Support Group Income Protection and private medical insurance Gym on-site in London 7.5% pension contribution by the company Discretionary annual bonus up to 10% of base salary Talent referral bonus up to £5K
Oct 08, 2026
Full time
Hybrid - Minimum 3 days on site in London, Tower Bridge HQ About Hometrack At Hometrack, we're redefining the mortgage journey for lenders, brokers and borrowers. We deliver market-leading valuation and risk evaluation services across the property technology and financial technology industries. Our customers include 9 of the top 10 mortgage providers, as well as many others in financial services. Founded in 1999, we made our name with our Automated Valuation Model (AVM) and now provide more than 50 million automated valuations every year. We want to make Houseful more welcoming, fair and representative every day. We'll consider everyone who applies for this role in the same way, regardless of your ethnicity, colour, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, neurodiversity status, family or parental status, or how long you've spent unemployed. You will be responsible for maintaining and improving the industry leading Hometrack AVM (Automated Valuation Model to estimate the value of residential properties). We are always looking to innovate and better identify and understand what data makes a difference to property value and risk and how to incorporate this into our models and products. You'll be at home if you enjoy: Being responsible for the performance of our live models. Detecting model drift and deploying model improvements to ensure the reliability of our valuations for lender clients. Researching new datasets and advanced machine learning techniques that can be used to increase the accuracy of our property valuation model and improve our AI capabilities across our model and product range. Work collaboratively with fellow data scientists, ML Engineers, analysts, product managers and data engineers. Meeting with stakeholders to translate business needs into data science problems. You'll hit the ground running if you have: An advanced degree in Computer Science, Mathematics, Physics, or other quantitative discipline Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code. You worked in an R&D environment and/or you are intimately familiar with the fundamentals of the scientific research method: critical thinking, formulating hypotheses, running experiments, drawing conclusions etc. Experienced at identifying problems that can be solved with machine learning and delivering them from prototype through to production. Great communicator - convey complex ideas and solutions in clear, precise and accessible ways. Team player who cares about accelerating not only Hometrack's technical capabilities, but also empowering colleagues Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps. Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Comfortable working with Docker and containerised applications Experience using AWS or similar cloud computing platform Experience delivering machine learning solutions within regulated environments, including familiarity with Model Risk Management (MRM), governance, or model explainability. There's always room to grow and learn with our roles so please don't be put off if you don't have all of these skills and experiences. It's more important that you're passionate about our mission to improve the home moving and owning experience for everyone. Benefits Everyday Flex - greater flexibility over where and when you work 25 days annual leave + extra days for years of service Day off for volunteering & Digital detox day Festive Closure - business closed for period between Christmas and New Year Cycle to work and electric car schemes Free Calm App membership Enhanced Parental leave Fertility Treatment Financial Support Group Income Protection and private medical insurance Gym on-site in London 7.5% pension contribution by the company Discretionary annual bonus up to 10% of base salary Talent referral bonus up to £5K
Harnham - Data & Analytics Recruitment
Liverpool, Merseyside
Data Scientist £45,000 - £55,000 Merseyside (3 days a week in office) This is an excellent opportunity to join a growing Data Science function at a business investing heavily in its data and AI capabilities. You'll work on high-impact customer and commercial projects, helping to shape how machine learning is adopted across the organisation while gaining exposure to cutting-edge tools and a rapidly evolving data environment. THE COMPANY This organisation is investing heavily in its Data and AI capabilities, with a focus on building a scalable Data Science function that delivers real business impact. As Data Science becomes increasingly central to decision-making, you'll have the opportunity to work on high-profile customer and commercial projects with strong backing from senior leadership. They foster a collaborative, pragmatic culture where Data Scientists are encouraged to move beyond experimentation and deliver solutions that create measurable value. The focus is on deploying models into production and embedding data-driven thinking across the business. THE ROLE As a Data Scientist, you will work closely with senior stakeholders, analysts, engineers, and fellow Data Scientists to deliver machine learning solutions across a range of customer and commercial use cases. Specifically, you can expect to be involved in the following: Building and deploying predictive machine learning models Developing customer segmentation and customer lifetime value models Creating forecasting solutions to support business planning Delivering propensity and churn models to improve customer engagement Translating complex analytical findings into clear business recommendations Collaborating with engineering teams to support model deployment and operationalisation Supporting the development of a modern Data Science platform Working with cloud-based machine learning tools and technologies Engaging directly with stakeholders to understand challenges and define analytical solutions SKILLS AND EXPERIENCE The successful Data Scientist will have the following skills and experience: Strong commercial experience in Data Science and machine learning Advanced Python and SQL skills Experience using statistical modelling and predictive analytics techniques Knowledge of machine learning algorithms such as XGBoost and related ensemble methods Experience delivering projects across the full Data Science lifecycle, from problem definition through to deployment Ability to communicate technical concepts clearly to non-technical audiences Experience working with customer analytics, segmentation, churn, propensity modelling, forecasting, or related use cases Exposure to cloud environments such as Azure or GCP is beneficial Experience with Azure ML, Vertex AI, or similar machine learning platforms is advantageous BENEFITS The successful Data Scientist will receive the following benefits: Salary between £45,000 - £55,000 - depending on experience HOW TO APPLY Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
Oct 08, 2026
Full time
Data Scientist £45,000 - £55,000 Merseyside (3 days a week in office) This is an excellent opportunity to join a growing Data Science function at a business investing heavily in its data and AI capabilities. You'll work on high-impact customer and commercial projects, helping to shape how machine learning is adopted across the organisation while gaining exposure to cutting-edge tools and a rapidly evolving data environment. THE COMPANY This organisation is investing heavily in its Data and AI capabilities, with a focus on building a scalable Data Science function that delivers real business impact. As Data Science becomes increasingly central to decision-making, you'll have the opportunity to work on high-profile customer and commercial projects with strong backing from senior leadership. They foster a collaborative, pragmatic culture where Data Scientists are encouraged to move beyond experimentation and deliver solutions that create measurable value. The focus is on deploying models into production and embedding data-driven thinking across the business. THE ROLE As a Data Scientist, you will work closely with senior stakeholders, analysts, engineers, and fellow Data Scientists to deliver machine learning solutions across a range of customer and commercial use cases. Specifically, you can expect to be involved in the following: Building and deploying predictive machine learning models Developing customer segmentation and customer lifetime value models Creating forecasting solutions to support business planning Delivering propensity and churn models to improve customer engagement Translating complex analytical findings into clear business recommendations Collaborating with engineering teams to support model deployment and operationalisation Supporting the development of a modern Data Science platform Working with cloud-based machine learning tools and technologies Engaging directly with stakeholders to understand challenges and define analytical solutions SKILLS AND EXPERIENCE The successful Data Scientist will have the following skills and experience: Strong commercial experience in Data Science and machine learning Advanced Python and SQL skills Experience using statistical modelling and predictive analytics techniques Knowledge of machine learning algorithms such as XGBoost and related ensemble methods Experience delivering projects across the full Data Science lifecycle, from problem definition through to deployment Ability to communicate technical concepts clearly to non-technical audiences Experience working with customer analytics, segmentation, churn, propensity modelling, forecasting, or related use cases Exposure to cloud environments such as Azure or GCP is beneficial Experience with Azure ML, Vertex AI, or similar machine learning platforms is advantageous BENEFITS The successful Data Scientist will receive the following benefits: Salary between £45,000 - £55,000 - depending on experience HOW TO APPLY Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
Data Scientist £45,000 - £55,000 Merseyside (3 days a week in office) This is an excellent opportunity to join a growing Data Science function at a business investing heavily in its data and AI capabilities. You'll work on high-impact customer and commercial projects, helping to shape how machine learning is adopted across the organisation while gaining exposure to cutting-edge tools and a rapidly evolving data environment. THE COMPANY This organisation is investing heavily in its Data and AI capabilities, with a focus on building a scalable Data Science function that delivers real business impact. As Data Science becomes increasingly central to decision-making, you'll have the opportunity to work on high-profile customer and commercial projects with strong backing from senior leadership. They foster a collaborative, pragmatic culture where Data Scientists are encouraged to move beyond experimentation and deliver solutions that create measurable value. The focus is on deploying models into production and embedding data-driven thinking across the business. THE ROLE As a Data Scientist, you will work closely with senior stakeholders, analysts, engineers, and fellow Data Scientists to deliver machine learning solutions across a range of customer and commercial use cases. Specifically, you can expect to be involved in the following: Building and deploying predictive machine learning models Developing customer segmentation and customer lifetime value models Creating forecasting solutions to support business planning Delivering propensity and churn models to improve customer engagement Translating complex analytical findings into clear business recommendations Collaborating with engineering teams to support model deployment and operationalisation Supporting the development of a modern Data Science platform Working with cloud-based machine learning tools and technologies Engaging directly with stakeholders to understand challenges and define analytical solutions SKILLS AND EXPERIENCE The successful Data Scientist will have the following skills and experience: Strong commercial experience in Data Science and machine learning Advanced Python and SQL skills Experience using statistical modelling and predictive analytics techniques Knowledge of machine learning algorithms such as XGBoost and related ensemble methods Experience delivering projects across the full Data Science lifecycle, from problem definition through to deployment Ability to communicate technical concepts clearly to non-technical audiences Experience working with customer analytics, segmentation, churn, propensity modelling, forecasting, or related use cases Exposure to cloud environments such as Azure or GCP is beneficial Experience with Azure ML, Vertex AI, or similar machine learning platforms is advantageous BENEFITS The successful Data Scientist will receive the following benefits: Salary between £45,000 - £55,000 - depending on experience HOW TO APPLY Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
Oct 08, 2026
Full time
Data Scientist £45,000 - £55,000 Merseyside (3 days a week in office) This is an excellent opportunity to join a growing Data Science function at a business investing heavily in its data and AI capabilities. You'll work on high-impact customer and commercial projects, helping to shape how machine learning is adopted across the organisation while gaining exposure to cutting-edge tools and a rapidly evolving data environment. THE COMPANY This organisation is investing heavily in its Data and AI capabilities, with a focus on building a scalable Data Science function that delivers real business impact. As Data Science becomes increasingly central to decision-making, you'll have the opportunity to work on high-profile customer and commercial projects with strong backing from senior leadership. They foster a collaborative, pragmatic culture where Data Scientists are encouraged to move beyond experimentation and deliver solutions that create measurable value. The focus is on deploying models into production and embedding data-driven thinking across the business. THE ROLE As a Data Scientist, you will work closely with senior stakeholders, analysts, engineers, and fellow Data Scientists to deliver machine learning solutions across a range of customer and commercial use cases. Specifically, you can expect to be involved in the following: Building and deploying predictive machine learning models Developing customer segmentation and customer lifetime value models Creating forecasting solutions to support business planning Delivering propensity and churn models to improve customer engagement Translating complex analytical findings into clear business recommendations Collaborating with engineering teams to support model deployment and operationalisation Supporting the development of a modern Data Science platform Working with cloud-based machine learning tools and technologies Engaging directly with stakeholders to understand challenges and define analytical solutions SKILLS AND EXPERIENCE The successful Data Scientist will have the following skills and experience: Strong commercial experience in Data Science and machine learning Advanced Python and SQL skills Experience using statistical modelling and predictive analytics techniques Knowledge of machine learning algorithms such as XGBoost and related ensemble methods Experience delivering projects across the full Data Science lifecycle, from problem definition through to deployment Ability to communicate technical concepts clearly to non-technical audiences Experience working with customer analytics, segmentation, churn, propensity modelling, forecasting, or related use cases Exposure to cloud environments such as Azure or GCP is beneficial Experience with Azure ML, Vertex AI, or similar machine learning platforms is advantageous BENEFITS The successful Data Scientist will receive the following benefits: Salary between £45,000 - £55,000 - depending on experience HOW TO APPLY Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
Senior Platform Engineer - DV Clearable - 5 Days On-Site Build and operate the platforms that make AI and machine learning work at scale We're looking for a Senior Platform Engineer to join our team and play a key role in designing and operating the platform that underpins AI and machine learning delivery . This is a hands-on senior platform role , focused on building robust, Kubernetes-based platforms that enable MLOps engineers, ML engineers, and data scientists to deploy, run, and manage models safely and effectively in production. While you'll need a strong understanding of how machine learning and LLM workloads are trained, packaged, deployed, and served, this is not a "deploy models all day" role . Instead, your impact will come from creating the infrastructure, tooling, workflows, and guardrails that allow others to do that work reliably and at scale. What you'll be doing You'll be responsible for building a production-grade AI / ML platform , not just running clusters. You will: Design, build, and operate a Kubernetes-based platform that supports multiple ML and engineering teams Extend Kubernetes with MLOps-specific capabilities , rather than treating it as a finished product Provideplatform-level support for: Model development and experimentation Model packaging, deployment, and promotion Scalable inference and LLM-based workloads Build shared platform services that enable consistent, repeatable model deployment , even where day-to-day deployment is owned by MLOps or ML engineers Work closely with data scientists and MLOps engineers to ensure the platform is genuinely usable and fit for purpose Own platform operability, reliability, security, and lifecycle management in production Troubleshoot complex issues that cut across infrastructure, Kubernetes, and MLOps layers Contribute to architectural decisions while remaining hands-on with implementation What we're looking for This role is ideal for someone who sees themselves first and foremost as a platform engineer , with the depth to support AI and ML workloads properly. Essential experience: Strong background as a Senior Platform Engineer or Senior DevOps Engineer Deep, hands-on experience building and operating Kubernetes-based platforms Strong practical experience with Helm and Infrastructure as Code (e.g. Terraform) Proven experience building internal platforms for other engineers , not just running workloads Strong grasp of operational fundamentals: monitoring, logging, reliability, incidents, and maintainability Comfortable collaborating closely with MLOps engineers and data scientists , even where responsibilities differ ML platform & MLOps knowledge (important) You don't need to be a full-time MLOps engineer - but you do need practical understanding of how ML and AI workloads behave in production. Experience or exposure to areas such as: MLOps platforms (e.g. Kubeflow or similar frameworks) Model serving and inference platforms (e.g. KServe, vLLM , or equivalent) Supporting LLM-based workloads , including performance and scaling considerations Notebook environments such as JupyterHub Awareness of emerging tooling around Responsible / Trustworthy AI or comparable solutions This ensures you're building a platform that actually works for AI use cases - not a generic compute layer. Desirable experience Working in organisations with a clear AI or data platform strategy Supporting data scientists or ML engineers at scale Experience in regulated, secure, or high-assurance environments Designing platforms that balance flexibility, governance, and control If you enjoy solving hard platform problems and understand that AI places real, specific demands on infrastructure, this role gives you the space and responsibility to make a genuine impact. If interested, apply now! Guidant, Carbon60, Lorien & SRG - The Vertage Group Portfolio are acting as an Employment Business in relation to this vacancy.
Oct 08, 2026
Full time
Senior Platform Engineer - DV Clearable - 5 Days On-Site Build and operate the platforms that make AI and machine learning work at scale We're looking for a Senior Platform Engineer to join our team and play a key role in designing and operating the platform that underpins AI and machine learning delivery . This is a hands-on senior platform role , focused on building robust, Kubernetes-based platforms that enable MLOps engineers, ML engineers, and data scientists to deploy, run, and manage models safely and effectively in production. While you'll need a strong understanding of how machine learning and LLM workloads are trained, packaged, deployed, and served, this is not a "deploy models all day" role . Instead, your impact will come from creating the infrastructure, tooling, workflows, and guardrails that allow others to do that work reliably and at scale. What you'll be doing You'll be responsible for building a production-grade AI / ML platform , not just running clusters. You will: Design, build, and operate a Kubernetes-based platform that supports multiple ML and engineering teams Extend Kubernetes with MLOps-specific capabilities , rather than treating it as a finished product Provideplatform-level support for: Model development and experimentation Model packaging, deployment, and promotion Scalable inference and LLM-based workloads Build shared platform services that enable consistent, repeatable model deployment , even where day-to-day deployment is owned by MLOps or ML engineers Work closely with data scientists and MLOps engineers to ensure the platform is genuinely usable and fit for purpose Own platform operability, reliability, security, and lifecycle management in production Troubleshoot complex issues that cut across infrastructure, Kubernetes, and MLOps layers Contribute to architectural decisions while remaining hands-on with implementation What we're looking for This role is ideal for someone who sees themselves first and foremost as a platform engineer , with the depth to support AI and ML workloads properly. Essential experience: Strong background as a Senior Platform Engineer or Senior DevOps Engineer Deep, hands-on experience building and operating Kubernetes-based platforms Strong practical experience with Helm and Infrastructure as Code (e.g. Terraform) Proven experience building internal platforms for other engineers , not just running workloads Strong grasp of operational fundamentals: monitoring, logging, reliability, incidents, and maintainability Comfortable collaborating closely with MLOps engineers and data scientists , even where responsibilities differ ML platform & MLOps knowledge (important) You don't need to be a full-time MLOps engineer - but you do need practical understanding of how ML and AI workloads behave in production. Experience or exposure to areas such as: MLOps platforms (e.g. Kubeflow or similar frameworks) Model serving and inference platforms (e.g. KServe, vLLM , or equivalent) Supporting LLM-based workloads , including performance and scaling considerations Notebook environments such as JupyterHub Awareness of emerging tooling around Responsible / Trustworthy AI or comparable solutions This ensures you're building a platform that actually works for AI use cases - not a generic compute layer. Desirable experience Working in organisations with a clear AI or data platform strategy Supporting data scientists or ML engineers at scale Experience in regulated, secure, or high-assurance environments Designing platforms that balance flexibility, governance, and control If you enjoy solving hard platform problems and understand that AI places real, specific demands on infrastructure, this role gives you the space and responsibility to make a genuine impact. If interested, apply now! Guidant, Carbon60, Lorien & SRG - The Vertage Group Portfolio are acting as an Employment Business in relation to this vacancy.
We're looking for an experienced Data Engineer to join our client's growing team, with a particular focus on Snowflake, data quality and data pipeline development. This is a permanent opportunity, paying up to £75,000 with hybrid working, and bonus of up to 15%. You will have the chance to make a lasting contribution to the data engineering capability as the client goes through a pivotal growth period. Please note, this is a hybrid role where you will need to be in the office at least two days a week. The Role Our data environment is currently undergoing an exciting period of change. We are consolidating a number of existing Azure Functions and data processes into a more streamlined, scalable Snowflake-based data platform. As a Data Engineer, you'll play a key role in this transition, helping to migrate existing pipelines and processes into Snowflake while ensuring the quality, reliability and usability of our data. You'll also work closely with our Data Scientists, supporting feature engineering and helping to make sure the data they need is accurate, accessible and fit for purpose. Key Responsibilities Support the migration and consolidation of existing data pipelines and processes into Snowflake. Develop and maintain robust, scalable data pipelines within the Snowflake environment. Work with existing Azure Functions and help identify opportunities to consolidate and improve the current architecture. Implement and improve data quality and validation processes using dbt. Develop data models and transformation processes to support analytical and data science requirements. Work closely with Data Scientists to support feature engineering and the development of data-driven solutions. Troubleshoot data pipeline and quality issues and ensure reliable data delivery. Contribute to the ongoing development of our data engineering practices, standards and architecture. About You We're looking for someone with a strong background in data engineering who enjoys working in an environment where there is an opportunity to shape and improve the way data is managed. You'll ideally have experience with: Snowflake and cloud-based data platforms. Building and maintaining data pipelines. dbt and data quality/testing frameworks. Azure, particularly Azure Functions or similar cloud-based services. SQL and data transformation. Data modelling and engineering for analytical use cases. Working collaboratively with Data Scientists, Analysts and wider technology teams. Experience supporting data migration or platform consolidation projects would be highly advantageous. On Offer Salary - up to £75,000 Hybrid working - minimum of 2 days a week in Windsor Up to 10% employer pension contribution PMI Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to diversity, equity and inclusion. Suitable candidates with equivalent qualifications and more or less experience can apply. Rates of pay and salary ranges are dependent upon your experience, qualifications and training. If you wish to apply, please read our Privacy Notice describing how we may process, disclose and store your personal data:
Oct 08, 2026
Full time
We're looking for an experienced Data Engineer to join our client's growing team, with a particular focus on Snowflake, data quality and data pipeline development. This is a permanent opportunity, paying up to £75,000 with hybrid working, and bonus of up to 15%. You will have the chance to make a lasting contribution to the data engineering capability as the client goes through a pivotal growth period. Please note, this is a hybrid role where you will need to be in the office at least two days a week. The Role Our data environment is currently undergoing an exciting period of change. We are consolidating a number of existing Azure Functions and data processes into a more streamlined, scalable Snowflake-based data platform. As a Data Engineer, you'll play a key role in this transition, helping to migrate existing pipelines and processes into Snowflake while ensuring the quality, reliability and usability of our data. You'll also work closely with our Data Scientists, supporting feature engineering and helping to make sure the data they need is accurate, accessible and fit for purpose. Key Responsibilities Support the migration and consolidation of existing data pipelines and processes into Snowflake. Develop and maintain robust, scalable data pipelines within the Snowflake environment. Work with existing Azure Functions and help identify opportunities to consolidate and improve the current architecture. Implement and improve data quality and validation processes using dbt. Develop data models and transformation processes to support analytical and data science requirements. Work closely with Data Scientists to support feature engineering and the development of data-driven solutions. Troubleshoot data pipeline and quality issues and ensure reliable data delivery. Contribute to the ongoing development of our data engineering practices, standards and architecture. About You We're looking for someone with a strong background in data engineering who enjoys working in an environment where there is an opportunity to shape and improve the way data is managed. You'll ideally have experience with: Snowflake and cloud-based data platforms. Building and maintaining data pipelines. dbt and data quality/testing frameworks. Azure, particularly Azure Functions or similar cloud-based services. SQL and data transformation. Data modelling and engineering for analytical use cases. Working collaboratively with Data Scientists, Analysts and wider technology teams. Experience supporting data migration or platform consolidation projects would be highly advantageous. On Offer Salary - up to £75,000 Hybrid working - minimum of 2 days a week in Windsor Up to 10% employer pension contribution PMI Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to diversity, equity and inclusion. Suitable candidates with equivalent qualifications and more or less experience can apply. Rates of pay and salary ranges are dependent upon your experience, qualifications and training. If you wish to apply, please read our Privacy Notice describing how we may process, disclose and store your personal data:
Let's begin! Senior Software Engineer-AI (14867) 5+ years of software engineering experience designing, coding, testing, and operating production-grade backend services and cloud-native applications Strong coding proficiency in TypeScript, Python, C#, or similar technologies, with experience building scalable application programming interfaces, microservices, and distributed systems Practical experience building enterprise AI applications using large language models, including agents, retrieval augmented generation, orchestration frameworks, and model optimization Demonstrated ability to own services, components, or features end to end, from technical design through production deployment and ongoing operation with limited supervision Hands-on experience with cloud-native technologies, serverless applications, event-driven architectures, data pipelines, relational and NoSQL databases, vector databases, observability tooling, and automated deployment pipelines Solid understanding of algorithms, data structures, scalability, reliability, performance optimization, security best practices, and engineering trade-offs Experience mentoring engineers through code review, pairing, debugging, documentation, and the promotion of engineering excellence through testing and continuous improvement practices Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use Education Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience Responsibilities Designs, builds, and operates the services and AI-powered features behind Moody's intelligent data products as a senior contributor within the Digital Content and Innovation organization. Design, code, test, and operate backend services, application programming interfaces, data pipelines, and inference pipelines that support real-time and batch AI workloads Own the delivery of assigned features and components end to end, from technical design through deployment, monitoring, production support, and continuous improvement Build and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integration Contribute to technical designs, participate in design reviews, and identify risks, constraints, trade-offs, and alternative approaches Maintain engineering excellence through automated testing, code reviews, observability, monitoring, alerting, operational readiness, and participation in on-call support Apply machine learning operations practices, including prompt versioning, automated evaluation, deployment pipelines, monitoring, and production issue resolution Partner closely with product managers, data scientists, machine learning engineers, and fellow engineers to translate requirements into reliable software solutions Mentor engineers, contribute to shared frameworks and developer tooling, document system designs and operational runbooks, and promote responsible AI practices across delivered features About the Team Our Digital Content and Innovation (DC&I) team is responsible for building next-generation internal and external products powered by cutting-edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing. The group brings together engineers, data scientists, and AI specialists to solve complex challenges and turn breakthrough ideas into practical products that enhance productivity, unlock insights, and create measurable business impact. Collaboration is central to how the team works. Engineers contribute across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while helping shape reusable platforms, frameworks, and responsible AI practices. By joining the team, you will work on some of the most exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth.
Oct 08, 2026
Full time
Let's begin! Senior Software Engineer-AI (14867) 5+ years of software engineering experience designing, coding, testing, and operating production-grade backend services and cloud-native applications Strong coding proficiency in TypeScript, Python, C#, or similar technologies, with experience building scalable application programming interfaces, microservices, and distributed systems Practical experience building enterprise AI applications using large language models, including agents, retrieval augmented generation, orchestration frameworks, and model optimization Demonstrated ability to own services, components, or features end to end, from technical design through production deployment and ongoing operation with limited supervision Hands-on experience with cloud-native technologies, serverless applications, event-driven architectures, data pipelines, relational and NoSQL databases, vector databases, observability tooling, and automated deployment pipelines Solid understanding of algorithms, data structures, scalability, reliability, performance optimization, security best practices, and engineering trade-offs Experience mentoring engineers through code review, pairing, debugging, documentation, and the promotion of engineering excellence through testing and continuous improvement practices Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use Education Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience Responsibilities Designs, builds, and operates the services and AI-powered features behind Moody's intelligent data products as a senior contributor within the Digital Content and Innovation organization. Design, code, test, and operate backend services, application programming interfaces, data pipelines, and inference pipelines that support real-time and batch AI workloads Own the delivery of assigned features and components end to end, from technical design through deployment, monitoring, production support, and continuous improvement Build and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integration Contribute to technical designs, participate in design reviews, and identify risks, constraints, trade-offs, and alternative approaches Maintain engineering excellence through automated testing, code reviews, observability, monitoring, alerting, operational readiness, and participation in on-call support Apply machine learning operations practices, including prompt versioning, automated evaluation, deployment pipelines, monitoring, and production issue resolution Partner closely with product managers, data scientists, machine learning engineers, and fellow engineers to translate requirements into reliable software solutions Mentor engineers, contribute to shared frameworks and developer tooling, document system designs and operational runbooks, and promote responsible AI practices across delivered features About the Team Our Digital Content and Innovation (DC&I) team is responsible for building next-generation internal and external products powered by cutting-edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing. The group brings together engineers, data scientists, and AI specialists to solve complex challenges and turn breakthrough ideas into practical products that enhance productivity, unlock insights, and create measurable business impact. Collaboration is central to how the team works. Engineers contribute across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while helping shape reusable platforms, frameworks, and responsible AI practices. By joining the team, you will work on some of the most exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth.
Hometrack is seeking a data scientist to maintain and enhance its Automated Valuation Model (AVM) and related ML systems in a hybrid London-based role. You will monitor model performance, explore new data sources, and collaborate with data scientists, ML engineers, analysts, product managers and engineers to drive better valuations. You should bring an advanced quantitative degree and a strong Python background, with experience from an R&D or ML development environment.
Oct 08, 2026
Full time
Hometrack is seeking a data scientist to maintain and enhance its Automated Valuation Model (AVM) and related ML systems in a hybrid London-based role. You will monitor model performance, explore new data sources, and collaborate with data scientists, ML engineers, analysts, product managers and engineers to drive better valuations. You should bring an advanced quantitative degree and a strong Python background, with experience from an R&D or ML development environment.
