Top Data Jobs in London

Lead and grow the UK data organisation (Data Science, ML Engineering, Analytics Engineering, Data Engineering). Set strategy, priorities, and operating model; partner with product, commercial, clinical and ops stakeholders; drive international platform migrations (Databricks/Redshift to GCP), support new market launches, provide technical and architectural leadership, and build a high-performing team.

Design, build, and maintain petabyte-scale batch and streaming data pipelines for robotics foundation model training and evaluation. Own data models, storage, ingestion, transformation, and orchestration. Standardize data models and unify processing across teleoperation and simulation datasets. Collaborate with a team building general-purpose Physical AI.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.

Build, maintain and improve scalable ETL/ELT pipelines, data warehouses and streaming systems. Ensure data modelling meets analytics and data science needs, uphold data engineering best practices (testing, CI/CD, observability, IaC), and collaborate across teams to deliver the technical roadmap and platform improvements.

Build and maintain data pipelines and ETL processes using Python and SQL; transform and model data with dbt and Snowflake; automate workflows, create tools to optimise operations, and collaborate with technical and non-technical stakeholders.

Own product-area metrics and funnels, find user drop-offs and opportunities, design and run A/B and growth experiments, build instrumentation/semantic models and analytics systems, ensure data quality and lineage, and work directly with PMs and engineers to turn insights into shipped product outcomes.

Own pricing and packaging analytics: build unit-economics, willingness-to-pay, and price-sensitivity models; design and run pricing experiments; operationalize pricing systems (eg. personalized discounting); and partner with finance, product, and growth to sequence and ship revenue-impacting changes.

Own the full growth funnel—from acquisition to expansion—identify high-leverage opportunities, design and run experiments, build instrumentation and agents to surface growth signals, and work closely with growth engineers to ship experiments that move metrics and drive measurable product growth.

Lead pricing-focused data science work: develop and deploy ML models for claims, fraud and risk KPIs; perform deep portfolio analysis using diverse datasets; own end-to-end delivery from concept to production; identify new data opportunities and mentor junior analysts.

Develop and deploy pricing and risk models for motor insurance using diverse datasets. Own end-to-end ML projects from EDA to production, evaluate post-deployment performance, identify new data opportunities, and mentor junior analysts to improve pricing, claims prediction and fraud detection.

Support daily asset allocation and portfolio rebalancing for DC clients, investigate client and internal queries, maintain procedures and controls, analyse data for discrepancies and improvements, support reporting and monitoring, assist technology/process enhancements, and collaborate across teams to deliver accurate operational and client outcomes.

Lead automation design across EMEA from concept to delivery: develop secure, scalable SCADA/PLC architectures, design OT networks, ensure IEC62443 alignment, review designs, troubleshoot live sites, produce technical documentation, and develop/test PLC and SCADA code libraries.

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 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.

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.

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.

Partner with FP&A and senior stakeholders to deliver commercial and strategic analysis, own trading insights and executive KPIs, build and automate dashboards, develop end-to-end data models and pipelines (dbt), and enable AI-driven self-serve analytics for business decisions.

Mid-level Data Scientist (2–5 years) focused on risk, fraud, and compliance. Build and deploy ML models and deterministic rules, run funnel and A/B experiment analyses, create dashboards, partner with Product/Growth/Engineering, and improve data quality and instrumentation.

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.

Senior technical authority for electrical engineering across EMEA data centre portfolio. Lead design governance, resilience validation, technical assurance, and delivery of HV/MV/LV, UPS, generator, protection, and energy systems from concept through commissioning. Drive reference designs, standards, consultant oversight, innovation (battery storage, liquid cooling), and cross-functional alignment to ensure constructability, operational readiness, and long-term platform performance.

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.

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 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.