Senior Data Engineer - Analytics (Contract) Hybrid - London/Reading A data engineer is required to deliver insight-ready datasets and support advanced analytics across a cloud-based environment. The role focuses on building scalable pipelines, refining complex data sources, and enabling analysts and data scientists with high-quality, well-structured data. Key Responsibilities Develop and optimise data pipelines for analytics and modelling. Cleanse, transform, and analyse large datasets using Python/R . Maintain SQL-driven processing workflows in the cloud. Perform EDA to identify trends, anomalies, and data issues. Collaborate with BI teams to deliver reliable analytical datasets. Skills & Experience Strong SQL and data wrangling. Proficient in Python or R. Experience with large, complex datasets and Power BI. AWS experience preferred: Glue, S3, Athena, Lambda, Redshift, Step Functions . Advantageous: statistics/ML exposure and telecom-style data environments. Contract: 6-month rolling, hybrid onsite - £500 - £550 p/d (Outside IR35)
Mar 27, 2026
Contractor
Senior Data Engineer - Analytics (Contract) Hybrid - London/Reading A data engineer is required to deliver insight-ready datasets and support advanced analytics across a cloud-based environment. The role focuses on building scalable pipelines, refining complex data sources, and enabling analysts and data scientists with high-quality, well-structured data. Key Responsibilities Develop and optimise data pipelines for analytics and modelling. Cleanse, transform, and analyse large datasets using Python/R . Maintain SQL-driven processing workflows in the cloud. Perform EDA to identify trends, anomalies, and data issues. Collaborate with BI teams to deliver reliable analytical datasets. Skills & Experience Strong SQL and data wrangling. Proficient in Python or R. Experience with large, complex datasets and Power BI. AWS experience preferred: Glue, S3, Athena, Lambda, Redshift, Step Functions . Advantageous: statistics/ML exposure and telecom-style data environments. Contract: 6-month rolling, hybrid onsite - £500 - £550 p/d (Outside IR35)
PySpark Engineer Lead As the Technical Lead, you will drive the high-stakes migration of legacy SAS analytics to a modern, cloud-native PySpark ecosystem on AWS. This isn't just a lift and shift you will refactor complex procedural logic into scalable, production-ready distributed pipelines for a Tier-1 financial services environment. Core Responsibilities Engineering Leadership: Design and develop complex ETL/ELT pipelines and Data Marts using PySpark, EMR, and Glue. Legacy Modernisation: Architect the conversion of SAS Base/Macros into modular, testable Python code using SAS2PY and manual refactoring. Performance Tuning: Optimise Spark execution (partitioning, shuffling, caching) to ensure cost-efficient processing of massive financial datasets. Quality & Governance: Implement rigorous CI/CD, unit testing, and data reconciliation frameworks to ensure "penny-perfect" accuracy. Technical Stack Engine: PySpark (Expert), Python (Clean Code/SOLID principles). AWS: EMR, Glue, S3, Athena, IAM, Lambda. Data Modeling: SCD Type 2, Fact/Dimension tables, Data Vault/Star Schema. Legacy: Proficiency in reading/debugging SAS (Base, Macros, DI Studio). DevOps: Git-based workflows, Jenkins/GitLab CI, Terraform. Randstad Technologies is acting as an Employment Business in relation to this vacancy.
Mar 15, 2026
Contractor
PySpark Engineer Lead As the Technical Lead, you will drive the high-stakes migration of legacy SAS analytics to a modern, cloud-native PySpark ecosystem on AWS. This isn't just a lift and shift you will refactor complex procedural logic into scalable, production-ready distributed pipelines for a Tier-1 financial services environment. Core Responsibilities Engineering Leadership: Design and develop complex ETL/ELT pipelines and Data Marts using PySpark, EMR, and Glue. Legacy Modernisation: Architect the conversion of SAS Base/Macros into modular, testable Python code using SAS2PY and manual refactoring. Performance Tuning: Optimise Spark execution (partitioning, shuffling, caching) to ensure cost-efficient processing of massive financial datasets. Quality & Governance: Implement rigorous CI/CD, unit testing, and data reconciliation frameworks to ensure "penny-perfect" accuracy. Technical Stack Engine: PySpark (Expert), Python (Clean Code/SOLID principles). AWS: EMR, Glue, S3, Athena, IAM, Lambda. Data Modeling: SCD Type 2, Fact/Dimension tables, Data Vault/Star Schema. Legacy: Proficiency in reading/debugging SAS (Base, Macros, DI Studio). DevOps: Git-based workflows, Jenkins/GitLab CI, Terraform. Randstad Technologies is acting as an Employment Business in relation to this vacancy.
Position Details School of Biosciences Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £47,389 to £56,535 with potential progression once in post to £63,606 Grade: 8 Full Time, Permanent Closing date: 31st March 2026 5 Positions Available Academic Development Programme - new Assistant Professors will undertake a 5-year development programme, at the end of which they are expected to be promoted to Associate Professor. The programme consists of a variety of development opportunities and the time to reflect and develop. Background We are seeking to appoint Assistant or Associate Professors in the School of Biosciences at the University of Birmingham. Their scientific expertise can relate to the any of following areas: engineering biology, epigenetics, mycology, plant science, or RNA biology. Individuals whose research has a demonstrable impact outside academia or strong potential for translation and application are of particular interest. These positions are part of a strategic realignment of research in the School of Biosciences. Building on existing strengths in microbiology, plant science, environmental genomics and toxicology, as well as structural and molecular cell biology, the School is adopting three broad, challenge-led research priorities: Understanding the Rules of Life, Addressing Global Change, and Sustainable Biology. The advertised post will be in the Research and Education category. We are looking for excellence in research and education with a commitment to school service via good citizenship and leadership. We welcome innovative and impactful research in both fundamental and applied areas. Evidence of a developing track record in publishing work of high academic quality and impact is essential, as is an emerging portfolio (or clear potential) of external research funding. Applicants must have a commitment to delivering excellent, inclusive teaching and learning at undergraduate and postgraduate levels. Teaching may include a range of contributions, notably within our Biotechnology, Biochemistry, Biological Sciences, Human Sciences, and Microbiology programmes. Applicants are also expected to have a commitment to postgraduate research supervision. Successful candidates will participate in School activities and take on responsibilities in academic self-governance appropriate to their appointment. There are significant opportunities for interdisciplinary collaboration across campus, via the Institute of Microbiology & Infection, the Birmingham Institute of Forest Research (BIFoR), the Centre for Environmental Research and Justice (CERJ), the Henry Wellcome Centre for Biomolecular NMR (HWB-NMR), the Birmingham Institute for Sustainability and Climate Action (BISCA) and the Institute for Data and AI (IDAI), as well as through global partnerships in Brazil, China, India, North America and Dubai. Role Summary The role holder will be based in Edgbaston. The key duties and responsibilities will include but not be limited to: giving lectures and seminars and supervising undergraduate / post graduate students, course development and innovation, taking an active part in examinations, carrying out innovative research and writing papers on topics relevant to the specialist subject area (this will include journals, books and other material), and obtaining research grant funding. The successful applicant will have a PhD in a relevant specialist subject area, as well as postdoctoral experience. We are looking for candidates who will actively contribute to our portfolio and community, through pursuit of research that will bring new opportunities, synergies, and interdisciplinary collaboration. The successful candidate will also have a track record in teaching at a higher education institution. Appointments will be made at either an Assistant Professor or Associate Professor level please specify which role you are applying for in the application. Use of AI in Applications We want to understand your genuine interest in the role and for the written elements of your application to accurately reflect your own communication style. Applications that rely too heavily on AI tools can appear generic and lack the detail we need to assess your skills and experience. Such applications will unlikely be progressed to interview. Diversity, Equality and Sustainability We believe there is no such thing as a 'typical' member of University of Birmingham staff and that diversity in its many forms is a strength that underpins the exchange of ideas, innovation and debate at the heart of University life. We are committed to proactively addressing the barriers experienced by some groups in our community and are proud to hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We have an Equality, Diversity and Inclusion Centre that focuses on continuously improving the University as a fair and inclusive place to work where everyone has the opportunity to succeed. We are also committed to sustainability, which is a key part of our strategy. Informal enquiries to James McDonald, email:
Mar 12, 2026
Full time
Position Details School of Biosciences Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £47,389 to £56,535 with potential progression once in post to £63,606 Grade: 8 Full Time, Permanent Closing date: 31st March 2026 5 Positions Available Academic Development Programme - new Assistant Professors will undertake a 5-year development programme, at the end of which they are expected to be promoted to Associate Professor. The programme consists of a variety of development opportunities and the time to reflect and develop. Background We are seeking to appoint Assistant or Associate Professors in the School of Biosciences at the University of Birmingham. Their scientific expertise can relate to the any of following areas: engineering biology, epigenetics, mycology, plant science, or RNA biology. Individuals whose research has a demonstrable impact outside academia or strong potential for translation and application are of particular interest. These positions are part of a strategic realignment of research in the School of Biosciences. Building on existing strengths in microbiology, plant science, environmental genomics and toxicology, as well as structural and molecular cell biology, the School is adopting three broad, challenge-led research priorities: Understanding the Rules of Life, Addressing Global Change, and Sustainable Biology. The advertised post will be in the Research and Education category. We are looking for excellence in research and education with a commitment to school service via good citizenship and leadership. We welcome innovative and impactful research in both fundamental and applied areas. Evidence of a developing track record in publishing work of high academic quality and impact is essential, as is an emerging portfolio (or clear potential) of external research funding. Applicants must have a commitment to delivering excellent, inclusive teaching and learning at undergraduate and postgraduate levels. Teaching may include a range of contributions, notably within our Biotechnology, Biochemistry, Biological Sciences, Human Sciences, and Microbiology programmes. Applicants are also expected to have a commitment to postgraduate research supervision. Successful candidates will participate in School activities and take on responsibilities in academic self-governance appropriate to their appointment. There are significant opportunities for interdisciplinary collaboration across campus, via the Institute of Microbiology & Infection, the Birmingham Institute of Forest Research (BIFoR), the Centre for Environmental Research and Justice (CERJ), the Henry Wellcome Centre for Biomolecular NMR (HWB-NMR), the Birmingham Institute for Sustainability and Climate Action (BISCA) and the Institute for Data and AI (IDAI), as well as through global partnerships in Brazil, China, India, North America and Dubai. Role Summary The role holder will be based in Edgbaston. The key duties and responsibilities will include but not be limited to: giving lectures and seminars and supervising undergraduate / post graduate students, course development and innovation, taking an active part in examinations, carrying out innovative research and writing papers on topics relevant to the specialist subject area (this will include journals, books and other material), and obtaining research grant funding. The successful applicant will have a PhD in a relevant specialist subject area, as well as postdoctoral experience. We are looking for candidates who will actively contribute to our portfolio and community, through pursuit of research that will bring new opportunities, synergies, and interdisciplinary collaboration. The successful candidate will also have a track record in teaching at a higher education institution. Appointments will be made at either an Assistant Professor or Associate Professor level please specify which role you are applying for in the application. Use of AI in Applications We want to understand your genuine interest in the role and for the written elements of your application to accurately reflect your own communication style. Applications that rely too heavily on AI tools can appear generic and lack the detail we need to assess your skills and experience. Such applications will unlikely be progressed to interview. Diversity, Equality and Sustainability We believe there is no such thing as a 'typical' member of University of Birmingham staff and that diversity in its many forms is a strength that underpins the exchange of ideas, innovation and debate at the heart of University life. We are committed to proactively addressing the barriers experienced by some groups in our community and are proud to hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We have an Equality, Diversity and Inclusion Centre that focuses on continuously improving the University as a fair and inclusive place to work where everyone has the opportunity to succeed. We are also committed to sustainability, which is a key part of our strategy. Informal enquiries to James McDonald, email:
Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies. We've evolved Fanatical Support to encompass the entire customer journey - providing Fanatical Experience from first consultation to daily operations. Our passionate experts combine the power of proactive, always on service and expertise with best in class tools and automation to deliver technology when and how our customers need it. We are seeking a highly accomplished Solution Director (Analytics & Al/ML) to lead the design and sales of two critical solution portfolios: Generative AI/LLM solutions and Data modernization/Lakehouse architectures on AWS. This pivotal role requires mastery of both domains - leveraging generative AI capabilities (Amazon Q, Amazon Bedrock, QuickSight) to drive executive conversations and opportunity creation, while delivering enterprise data modernization through Lakehouse architectures using AWS native services (Glue, SageMaker Unified Studio) and leading platforms (Databricks on AWS, Snowflake on AWS). This is a presales role that demands cross functional experience with proven ability to engage C level stakeholders, drive top of funnel opportunity creation, and maintain comprehensive account ownership across the entire customer lifecycle. The ideal candidate will excel at both selling the vision of generative AI transformation and delivering the reality of enterprise data modernization, combining deep technical expertise with exceptional business acumen and executive presence. Responsibilities Strategic Leadership & Opportunity Development • Drive top of funnel opportunity creation through two parallel tracks: engaging C level stakeholders with generative AI demonstrations (Amazon Q, Amazon Bedrock) and identifying data modernization needs for Lakehouse transformations. • Lead the design and architecture of dual solution portfolios: Generative AI Solutions: Amazon Bedrock implementations, Amazon Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions. Data Modernization: Enterprise Lakehouse architectures using AWS Glue, SageMaker Unified Studio, Databricks on AWS, and Snowflake on AWS. • Act as the trusted advisor, positioning generative AI as the transformational vision while grounding delivery in robust data platform modernization. • Develop compelling business cases that connect AI aspirations with practical data foundation requirements, demonstrating ROI across both portfolios. • Stay current with advancements in generative AI (foundation models, LLMs) and modern data architectures (Lakehouse patterns, data mesh, unified analytics). • Contribute to Rackspace's intellectual property through reference architectures covering both generative AI implementations and Lakehouse design patterns. • Mentor and provide leadership to Solution Architects by guiding technical development and fostering skill growth across both generative AI and data modernization solution areas. Customer Engagement & Solution Delivery • Serve as the primary technical lead orchestrating both generative AI discussions and data modernization programs for strategic accounts. • Build strategic relationships using two engagement models: Executive Level: Amazon Q demonstrations, QuickSight analytics with generative BI, art of the possible sessions. Technical Level: Lakehouse architecture workshops, platform assessments (Databricks vs Snowflake vs AWS native), migration planning. • Lead comprehensive consultative engagements that begin with generative AI vision (Amazon Q, Bedrock) and translate into concrete data modernization roadmaps. • Develop proposals that balance innovative AI capabilities with foundational data platform requirements. Guide customers through parallel journeys: generative AI adoption (POCs to production) and data platform modernization (legacy to Lakehouse). • Collaborate with sales teams to position both solution portfolios strategically based on customer maturity and needs. Technical Excellence & Market Awareness Maintain deep expertise across both solution domains: 1) Generative AI: Amazon Bedrock, Amazon Q, QuickSight Q, SageMaker JumpStart, prompt engineering, RAG architectures, vector databases. 2) Data Platforms: AWS Glue, SageMaker Unified Studio, Databricks on AWS, Snowflake on AWS, Redshift, EMR, Apache Iceberg, Delta Lake. • Position AWS solutions effectively against other cloud platforms' offerings in both generative AI (Azure OpenAI, Vertex AI) and data platforms (Azure Synapse, BigQuery). • Guide architectural decisions on build vs. buy for both AI capabilities and data platform components. Required Experience Deep experience with generative AI technologies: Amazon Bedrock, Amazon Q, LLM architectures, RAG implementations. Proven track record delivering data modernization: Lakehouse architectures, Databricks and/or Snowflake implementations, AWS Glue/EMR deployments. A bachelor's degree in computer science, Data Science, Engineering, Mathematics, or a related technical field is required. At the manager's discretion, additional relevant experience may substitute for the degree requirement. A minimum of 15 years of enterprise solution architecture experience. A minimum of 8 years of public cloud experience. A minimum of 5 years as a senior level architect or solutions leader with hands on experience in both AI/ML and data platform modernization. Proven Presales/Sales Engineering experience. Demonstrated success in engaging C level executives using generative AI demonstrations while delivering complex data platform transformations. Strong understanding across the full spectrum: AI/ML: Generative AI, foundation models, LLMs, traditional ML, prompt engineering, fine tuning. Data Platforms: Lakehouse architectures, data mesh, ETL/ELT, streaming, data governance, data quality. Proficiency in Python, SQL, and Spark with hands on experience in: Generative AI: LangChain, vector databases, embedding models. Data Engineering: PySpark, Apache Iceberg/Delta Lake, orchestration tools. A proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences. Preferred Qualifications An advanced degree (Master's or PhD) in a relevant field. Experience with AWS professional services or AWS partner ecosystem across both AI and data domains. Multiple Lakehouse platforms: Databricks, Snowflake, AWS native (Glue + Athena + Redshift). Multiple AI platforms: AWS Bedrock, Azure OpenAI, Google Vertex AI. Industry certifications: AWS - Solutions Architect Professional, Machine Learning Specialty, Data Analytics Specialty. Platform specific - Databricks Certified, Snowflake SnowPro. Experience with regulated industries requiring governance for both AI and data platforms. Track record building practices that deliver both generative AI solutions and data modernization programs. Published thought leadership in generative AI applications and/or modern data architectures.
Mar 11, 2026
Full time
Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies. We've evolved Fanatical Support to encompass the entire customer journey - providing Fanatical Experience from first consultation to daily operations. Our passionate experts combine the power of proactive, always on service and expertise with best in class tools and automation to deliver technology when and how our customers need it. We are seeking a highly accomplished Solution Director (Analytics & Al/ML) to lead the design and sales of two critical solution portfolios: Generative AI/LLM solutions and Data modernization/Lakehouse architectures on AWS. This pivotal role requires mastery of both domains - leveraging generative AI capabilities (Amazon Q, Amazon Bedrock, QuickSight) to drive executive conversations and opportunity creation, while delivering enterprise data modernization through Lakehouse architectures using AWS native services (Glue, SageMaker Unified Studio) and leading platforms (Databricks on AWS, Snowflake on AWS). This is a presales role that demands cross functional experience with proven ability to engage C level stakeholders, drive top of funnel opportunity creation, and maintain comprehensive account ownership across the entire customer lifecycle. The ideal candidate will excel at both selling the vision of generative AI transformation and delivering the reality of enterprise data modernization, combining deep technical expertise with exceptional business acumen and executive presence. Responsibilities Strategic Leadership & Opportunity Development • Drive top of funnel opportunity creation through two parallel tracks: engaging C level stakeholders with generative AI demonstrations (Amazon Q, Amazon Bedrock) and identifying data modernization needs for Lakehouse transformations. • Lead the design and architecture of dual solution portfolios: Generative AI Solutions: Amazon Bedrock implementations, Amazon Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions. Data Modernization: Enterprise Lakehouse architectures using AWS Glue, SageMaker Unified Studio, Databricks on AWS, and Snowflake on AWS. • Act as the trusted advisor, positioning generative AI as the transformational vision while grounding delivery in robust data platform modernization. • Develop compelling business cases that connect AI aspirations with practical data foundation requirements, demonstrating ROI across both portfolios. • Stay current with advancements in generative AI (foundation models, LLMs) and modern data architectures (Lakehouse patterns, data mesh, unified analytics). • Contribute to Rackspace's intellectual property through reference architectures covering both generative AI implementations and Lakehouse design patterns. • Mentor and provide leadership to Solution Architects by guiding technical development and fostering skill growth across both generative AI and data modernization solution areas. Customer Engagement & Solution Delivery • Serve as the primary technical lead orchestrating both generative AI discussions and data modernization programs for strategic accounts. • Build strategic relationships using two engagement models: Executive Level: Amazon Q demonstrations, QuickSight analytics with generative BI, art of the possible sessions. Technical Level: Lakehouse architecture workshops, platform assessments (Databricks vs Snowflake vs AWS native), migration planning. • Lead comprehensive consultative engagements that begin with generative AI vision (Amazon Q, Bedrock) and translate into concrete data modernization roadmaps. • Develop proposals that balance innovative AI capabilities with foundational data platform requirements. Guide customers through parallel journeys: generative AI adoption (POCs to production) and data platform modernization (legacy to Lakehouse). • Collaborate with sales teams to position both solution portfolios strategically based on customer maturity and needs. Technical Excellence & Market Awareness Maintain deep expertise across both solution domains: 1) Generative AI: Amazon Bedrock, Amazon Q, QuickSight Q, SageMaker JumpStart, prompt engineering, RAG architectures, vector databases. 2) Data Platforms: AWS Glue, SageMaker Unified Studio, Databricks on AWS, Snowflake on AWS, Redshift, EMR, Apache Iceberg, Delta Lake. • Position AWS solutions effectively against other cloud platforms' offerings in both generative AI (Azure OpenAI, Vertex AI) and data platforms (Azure Synapse, BigQuery). • Guide architectural decisions on build vs. buy for both AI capabilities and data platform components. Required Experience Deep experience with generative AI technologies: Amazon Bedrock, Amazon Q, LLM architectures, RAG implementations. Proven track record delivering data modernization: Lakehouse architectures, Databricks and/or Snowflake implementations, AWS Glue/EMR deployments. A bachelor's degree in computer science, Data Science, Engineering, Mathematics, or a related technical field is required. At the manager's discretion, additional relevant experience may substitute for the degree requirement. A minimum of 15 years of enterprise solution architecture experience. A minimum of 8 years of public cloud experience. A minimum of 5 years as a senior level architect or solutions leader with hands on experience in both AI/ML and data platform modernization. Proven Presales/Sales Engineering experience. Demonstrated success in engaging C level executives using generative AI demonstrations while delivering complex data platform transformations. Strong understanding across the full spectrum: AI/ML: Generative AI, foundation models, LLMs, traditional ML, prompt engineering, fine tuning. Data Platforms: Lakehouse architectures, data mesh, ETL/ELT, streaming, data governance, data quality. Proficiency in Python, SQL, and Spark with hands on experience in: Generative AI: LangChain, vector databases, embedding models. Data Engineering: PySpark, Apache Iceberg/Delta Lake, orchestration tools. A proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences. Preferred Qualifications An advanced degree (Master's or PhD) in a relevant field. Experience with AWS professional services or AWS partner ecosystem across both AI and data domains. Multiple Lakehouse platforms: Databricks, Snowflake, AWS native (Glue + Athena + Redshift). Multiple AI platforms: AWS Bedrock, Azure OpenAI, Google Vertex AI. Industry certifications: AWS - Solutions Architect Professional, Machine Learning Specialty, Data Analytics Specialty. Platform specific - Databricks Certified, Snowflake SnowPro. Experience with regulated industries requiring governance for both AI and data platforms. Track record building practices that deliver both generative AI solutions and data modernization programs. Published thought leadership in generative AI applications and/or modern data architectures.
Lead Data Scientist My client is a fast-growing UK FinTech business serving thousands of customers. They are investing heavily in their data capability and are now looking to appoint a Lead Data Scientist to drive end-to-end machine learning delivery within a regulated financial environment. This is a hands-on leadership role combining technical ownership, team development, and production-grade model deployment. The Role As Lead Data Scientist, you will: Lead and develop a growing Data Science team, setting standards and delivery cadence Own end-to-end ML solutions - from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone who thinks beyond experimentation - focusing on operational impact, adoption, and long-term model performance. Essential Experience Proven commercial ML/Data Science delivery with measurable impact Experience taking models into production and managing performance over time Prior experience leading or mentoring Data Scientists Strong Python (pandas, numpy, scikit-learn or similar) Strong SQL (complex joins, aggregations, analytical functions) Solid grounding in applied statistics, evaluation design, calibration, bias/fairness Experience working closely with Engineering/Data teams in production-first environments Comfortable operating within regulated industries Desirable AWS experience (S3, Athena/Glue, IAM, Lambda) SageMaker or equivalent ML platform experience Financial services domain knowledge (risk, fraud, affordability, payments) Experience with model explainability and governance documentation Package & Benefits Hybrid working model Competitive pension Additional paid leave (birthday, charity, wellbeing, life events) Employee assistance programme & Virtual GP Modern collaborative office environment Interested? Please Click Apply Now! Lead Data Scientist
Mar 06, 2026
Full time
Lead Data Scientist My client is a fast-growing UK FinTech business serving thousands of customers. They are investing heavily in their data capability and are now looking to appoint a Lead Data Scientist to drive end-to-end machine learning delivery within a regulated financial environment. This is a hands-on leadership role combining technical ownership, team development, and production-grade model deployment. The Role As Lead Data Scientist, you will: Lead and develop a growing Data Science team, setting standards and delivery cadence Own end-to-end ML solutions - from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone who thinks beyond experimentation - focusing on operational impact, adoption, and long-term model performance. Essential Experience Proven commercial ML/Data Science delivery with measurable impact Experience taking models into production and managing performance over time Prior experience leading or mentoring Data Scientists Strong Python (pandas, numpy, scikit-learn or similar) Strong SQL (complex joins, aggregations, analytical functions) Solid grounding in applied statistics, evaluation design, calibration, bias/fairness Experience working closely with Engineering/Data teams in production-first environments Comfortable operating within regulated industries Desirable AWS experience (S3, Athena/Glue, IAM, Lambda) SageMaker or equivalent ML platform experience Financial services domain knowledge (risk, fraud, affordability, payments) Experience with model explainability and governance documentation Package & Benefits Hybrid working model Competitive pension Additional paid leave (birthday, charity, wellbeing, life events) Employee assistance programme & Virtual GP Modern collaborative office environment Interested? Please Click Apply Now! Lead Data Scientist
