Top Data Jobs in London

The Associate Data Scientist will work on developing and optimizing machine learning models, collaborating with teams to tackle pricing and matching challenges.

Lead the development and integration of AI solutions, focusing on advanced modeling, generative AI architecture, and building user interfaces for decision-making tools.

Lead design and delivery of production-grade AI/ML solutions for Kainos Workday products. Build predictive analytics, anomaly detection, generative AI features, and scalable MLOps pipelines. Integrate with Workday, mentor and line-manage a data science team, manage client engagements, and drive architectural and technical leadership across product initiatives.

Support delivery of AI/ML solutions for Workday products by applying statistical and machine learning methods, building models and visualisations, assisting deployment alongside engineers, and collaborating with senior team members to learn and deliver on client projects.

Design and deliver production-grade AI/ML solutions for Kainos Workday products, including LLM-driven features, model deployment, dashboards, and mentoring junior staff. Collaborate with engineering and clients to improve product functionality, scalability, and efficiency.

Abstract and enter clinical data from health records, ensure data quality and confidentiality, use EHR/practice management systems and Microsoft Office, troubleshoot basic access/VPN/MFA issues, and collaborate with clinical teams to support operations.

Define and build quality frameworks for human data programs, partner with clients and engineering to design evaluation, recruitment and annotation strategies, implement automated checks and dashboards, investigate data integrity, and upskill teams to deliver high-quality human data at scale.

Lead design and delivery of a deterministic identity graph and graph-driven identity intelligence. Discover features from connected data, build link-analysis pipelines, prototype identity-resolution and fraud/risk models, define quality signals and ingestion workflows, align data capabilities with product goals, select graph technologies, document standards, and mentor/grow a data science team while shipping production-grade graph-enabled product features.

Lead multi-skilled agile teams to design, build and productionise modern data solutions. Own technical architecture, collaborate with infrastructure and customer architects, define functional and non-functional designs, mentor staff, estimate delivery timelines, contribute to data community and support pre-sales technical solutioning.

Lead and grow the data engineering and ML teams, own technical strategy and delivery for data infrastructure and model estate, translate business goals into scalable data and ML solutions, partner with product/marketing/commercial leadership, hire and develop engineers, and drive adoption of AI-led development while remaining hands-on.

Lead design and implementation of scalable generative AI services and reusable components using Python. Drive architectural decisions, deploy containerized applications on Kubernetes (EKS), ensure scalability/observability and CI/CD, mentor engineers, and collaborate with product and research teams to productionize LLM capabilities.

Work with stakeholders, product and technical teams to elicit, document, and translate business and data requirements into user stories and acceptance criteria. Support backlog refinement, run workshops, assist data analysis and validation, and identify process improvements to enable data-driven decisions.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

The Solution Architect will design and implement big data solutions for overseas clients, requiring expertise in various big data technologies and cloud services, as well as strong communication and technical presentation skills.

Hunt and close net-new enterprise accounts across the UK for a data/AI infrastructure platform. Own full sales cycle from pipeline generation to close, engage technical and economic buyers, partner with pre-sales and channel, manage forecasting and deal negotiations, and represent VAST at industry events.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

As a Graduate Data Scientist, you'll work on fraud detection, anti-money laundering, and claims automation, implementing data engineering and developing machine learning models.

The Graduate Data Scientist will support data advisory engagements by documenting data processes, constructing architecture diagrams, and communicating strategies to stakeholders. They will utilize databases, SQL, and cloud platforms.

Lead design and evolution of scalable real-time and batch ETL pipelines and data platform. Own performance, reliability, and data quality; drive architecture and tooling choices; collaborate with product and backend teams; mentor engineers and shape target architecture to support trader-facing analytics and low-latency data needs.

Collect, clean, and transform large datasets; build and maintain data models and reports (using Snowflake and BI tools); perform statistical and machine-learning analyses; define KPIs; ensure data governance and accuracy; present insights to stakeholders; collaborate with data engineers and follow software development best practices.

Lead data operations and governance for influencer campaigns: manage complex campaign configurations, ensure data quality and naming conventions, troubleshoot issues, build custom BI queries/dashboards, improve processes, support proprietary platform (IBEX), and mentor junior team members.

Lead a marketing science team to design and deploy advanced econometric and predictive models (MMM, Bayesian, ML) for media measurement, build scalable analytics frameworks, manage stakeholders, and drive methodological innovation and team development to optimize campaign performance.

Lead data operations and governance for influencer campaigns: manage complex campaign configurations, ensure data quality, troubleshoot issues, build and customize BI dashboards, optimise workflows, and mentor junior team members while supporting proprietary analytics platforms.

Lead the design and execution of advanced technical solutions for hyperscale and enterprise clients in data centers and AI environments, ensuring efficient, scalable solutions align with customer needs.

As a Data Engineer, you'll build and optimize data platforms, create data pipelines, and implement ML infrastructure to support business insights and data service needs.