TWG Global AI

A leading AI solutions provider is looking for a Senior Associate, Data Scientist to join their innovative team in the UK. In this hybrid position, you will design and develop data-driven models, working on important projects across various industries including financial services and insurance. Ideal candidates should possess at least 5 years of experience in data science with a strong command of statistical analyses and machine learning. Competitive compensation and a range of benefits are offered, along with opportunities for growth and development within a dynamic environment.

A leading technology and data firm seeks a Staff Data Scientist to lead impactful data science initiatives. You will design statistical models and machine learning techniques to drive business value, ensuring responsible AI practices while mentoring junior data scientists. Ideal candidates have 8+ years of experience and strong skills in Python, AI methodologies, and effective communication. This hybrid role is located in Greater London, offering competitive compensation and comprehensive benefits.

A leading AI firm in the United Kingdom is seeking a Staff Machine Learning Engineer (VP) to design and deploy advanced machine learning systems. You will lead the development of production-grade infrastructure and mentor a team of ML engineers. This hybrid role offers competitive compensation and a comprehensive benefits package while driving AI innovation in financial services. Candidates should possess strong ML expertise, a proven track record in the field, and a Master's or PhD in a relevant discipline.

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI first, cloud native approach delivers real time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As the Staff Data Scientist (VP) on the AI Science team, you will be responsible for designing and leading high impact data science initiatives that drive business value across the enterprise. Reporting to the Executive Director of AI Science, you will play a critical role in shaping data driven strategy, developing advanced statistical and machine learning models, and delivering insights that inform decision making, optimize operations, and uncover new growth opportunities. You will act as both a technical thought leader and a strategic partner, fostering a culture of rigorous experimentation, reproducibility, and responsible AI adoption while mentoring the next generation of data scientists. Key Responsibilities Lead the design and execution of data science projects that solve complex business problems across critical workflows. Develop and apply advanced AI/ML methods including statistical modeling, causal inference, forecasting, optimization, and machine learning. Partner with stakeholders to translate business challenges into analytical frameworks, ensuring results are actionable and aligned with strategic priorities. Drive the adoption of emerging analytical techniques and tools (e.g., generative AI, LLM based analytics, simulation modeling, RAG for knowledge discovery). Collaborate with ML engineers to scale prototypes into production ready systems, ensuring reliability, fairness, and generalizability. Design and maintain metrics and experiments (A/B testing, uplift modeling, KPI design) to measure model and business impact. Communicate findings through compelling data storytelling, dashboards, and executive level presentations. Provide thought leadership in responsible AI practices, ensuring transparency, fairness, and compliance with internal governance and external regulations. Mentor and guide other data scientists, fostering technical excellence, innovation, and collaboration across the team. Qualifications 8+ years of experience in data science or applied statistics roles, with a proven track record of driving measurable business impact. Expertise in one or more of supervised and unsupervised machine learning, deep learning, time series analysis, causal inference, and statistical modeling. Experience leading end to end data science projects from ideation to delivery, including business scoping and stakeholder management. Strong proficiency in Python (or R), with deep experience using modern data science libraries (e.g., Pandas, NumPy, scikit learn, PyTorch, TensorFlow, Statsmodels). Solid foundation in SQL and data wrangling across large, complex datasets. Hands on experience with experimentation platforms, data visualization, and dashboarding tools (e.g., Tableau, Power BI, Plotly). Familiarity with cloud based data platforms (AWS, GCP, Azure) and collaborative tools (Databricks, Snowflake) is a plus. Exceptional ability to translate technical results into clear, actionable insights for senior executives and non technical audiences. Master's or PhD in Statistics, Data Science, Computer Science, Economics, or a closely related discipline. Preferred Qualifications Experience working with Palantir platforms (Foundry, AIP, Ontology) to develop, analyze, and operationalize data driven insights within enterprise scale environments. PhD in Data Science, Statistics, Computer Science, or a related quantitative discipline. Publications in top tier AI/ML or data science conferences or journals (e.g., NeurIPS, ICML, KDD, AAAI, ACL, JASA). Recognized contributions to the open source data science / ML ecosystem (e.g., libraries, frameworks, toolkits, widely adopted notebooks). Track record of thought leadership through invited talks, keynote presentations, or leadership roles in professional societies, conferences, or meetups. Experience mentoring teams at scale and establishing standards for reproducibility, experimentation, and responsible AI. Familiarity with vector databases, knowledge graphs, and LLM application frameworks for advanced analytics. Cloud or AI/ML certifications (e.g., AWS ML Specialty, Google Cloud ML Engineer, Azure AI Engineer) are a plus. Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services. Drive AI transformation for some of the most sophisticated financial entities. Competitive compensation, benefits, future equity options, and leadership opportunities. This is a hybrid position based in the United Kingdom. We offer a competitive base pay + a discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

A technology solutions firm in the United Kingdom is seeking a Senior Associate, Machine Learning Engineer. You will design, build, and scale machine learning systems to drive business value. The role involves working with a dynamic AI team, contributing to ML models, and collaborating with data scientists. Ideal candidates will have experienced in deploying machine learning models and proficiency in Python, alongside relevant tools and technologies. This hybrid role offers competitive compensation, benefits, and career growth opportunities.

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI first, cloud native approach delivers real time intelligence and interactive business applications, empowering informed decision making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As a Senior Associate, Machine Learning Engineer, you'll work alongside experienced ML engineers and data scientists to design, build, and scale machine learning systems that deliver real business value. Reporting to the Executive Director of ML Engineering, you'll gain hands on experience developing production grade pipelines, monitoring frameworks, and scalable ML applications that support mission critical business functions. This is a high growth opportunity for someone with early industry experience (or strong academic grounding) in machine learning engineering, eager to deepen their expertise in production systems and MLOps while growing within a dynamic AI team operating at the frontier of applied ML. Key Responsibilities Contribute to the design, development, and deployment of ML models and pipelines across business critical domains such as financial services and insurance. Support production efforts, including model packaging, integration, CI/CD deployment, and monitoring for performance, drift, and reliability. Collaborate with senior engineers to build internal ML engineering tools and infrastructure that improve training, testing, and observability workflows. Partner with Data Scientists to operationalize prototype models, ensuring they are scalable, robust, and cost efficient in production. Work with large scale datasets to enable feature engineering, transformation, and quality assurance within ML pipelines. Implement monitoring dashboards, alerts, and diagnostics for model health and system performance. Contribute to documentation, governance, and reproducibility practices, supporting compliance in regulated environments. Qualifications 5+ years of experience building and deploying machine learning models in production environments, with exposure to monitoring and diagnostics. Solid understanding of machine learning engineering fundamentals (pipelines, deployment, monitoring) and familiarity with data science workflows. Experience with MLOps tools such as MLflow, Weights & Biases, or equivalent. Exposure to observability/monitoring systems (Prometheus, Grafana, ELK, Datadog) is a plus. Proficiency in Python and familiarity with ML libraries (scikit learn, XGBoost, TensorFlow, PyTorch). Strong experience with data manipulation and pipelines using Pandas, NumPy, and SQL. Knowledge of containerized deployments (Docker, Kubernetes) and cloud ML services (AWS SageMaker, GCP Vertex AI, or Azure ML) preferred. Excellent problem solving skills, eagerness to learn, and ability to thrive in a fast paced, evolving environment. Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field. Strong written and verbal communication skills, with the ability to explain technical details to both technical and business stakeholders. Preferred experience Hands on experience with Palantir platforms (Foundry, AIP, Ontology), including deploying and integrating ML solutions in enterprise ecosystems. Familiarity with vector databases (FAISS, Pinecone, Milvus, Weaviate) and LLM engineering workflows. Exposure to graph databases (Neo4j, TigerGraph) and their application in AI/ML systems. Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services. Drive AI transformation for some of the most sophisticated financial entities. Competitive compensation, benefits, future equity options, and leadership opportunities. This is a hybrid position based in the United Kingdom. We offer a competitive base pay + a discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI first, cloud native approach delivers real time intelligence and interactive business applications, empowering informed decision making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As the Staff Machine Learning Engineer (VP) on the ML Engineering team, you will be responsible for designing, deploying, and scaling advanced ML systems that power core business functions across the enterprise. Reporting to the Executive Director of ML Engineering, you will play a critical role in building production grade ML infrastructure, reusable frameworks, and scalable model pipelines that deliver measurable business outcomes-ranging from cost optimization to top line growth. You will act as a technical thought leader and strategic partner, shaping the organization's machine learning engineering practices and fostering a culture of operational excellence, reliability, and responsible AI adoption. Key Responsibilities Architect and deploy ML systems and platforms that solve high impact business problems across regulated enterprise environments. Lead the development of production ready pipelines, including feature stores, model registries, and scalable inference services. Champion MLOps best practices (CI/CD for ML, model versioning, monitoring, observability) to ensure models are reliable, reproducible, and cost efficient. Partner with Data Scientists to operationalize experimental models, enabling scalability and generalizability across diverse business domains. Integrate emerging ML engineering techniques (e.g., LLM deployment, fine tuning pipelines, vector databases, RAG systems) into enterprise ready solutions. Own the design of foundational ML platforms and frameworks that serve as building blocks for downstream AI applications. Embed controls, governance, and auditability into ML workflows, ensuring compliance with regulatory standards and responsible AI principles. Collaborate with Engineering, Product, and Security teams to embed ML driven decision making into enterprise platforms and workflows. Define and track engineering and model performance metrics (latency, scalability, cost, accuracy) to optimize systems in production. Mentor and coach ML engineers, fostering technical excellence, collaboration, and innovation within the AI Science team. Qualifications 8+ years of experience building and deploying machine learning systems in production environments at enterprise or platform scale. Proven track record of leading ML engineering projects from architecture to deployment, including ownership of production grade systems. Deep expertise in ML frameworks and engineering stacks (TensorFlow, PyTorch, JAX, Ray, MLflow, Kubeflow). Proficiency in Python and at least one backend language (e.g., Java, Scala, Go, C++). Strong understanding of cloud ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML) and containerized deployments (Kubernetes, Docker). Hands on experience with data and model pipelines (feature stores, registries, distributed training, inference scaling). Knowledge of observability and monitoring stacks (Prometheus, Grafana, ELK, Datadog) for ML system performance. Experience collaborating with cross functional teams in regulated industries (finance, insurance, health) with compliance and governance needs. Exceptional communication and leadership skills, with the ability to translate complex engineering challenges into clear business outcomes. Master's or PhD in Computer Science, Machine Learning, or related technical discipline. Preferred Qualifications Hands on experience with Palantir platforms (Foundry, AIP, Ontology), including developing, deploying, and integrating ML solutions in enterprise ecosystems. Exposure to LLM and GenAI engineering (fine tuning, vector search, distributed inference). Experience optimizing GPU clusters, distributed training, or HPC environments. Familiarity with graph databases (e.g., Neo4j, TigerGraph) and their application in AI/ML systems. Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services. Drive AI transformation for some of the most sophisticated financial entities. Competitive compensation, benefits, future equity options, and leadership opportunities. This is a hybrid position based in the United Kingdom. We offer a competitive base pay + a discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.