Top Data Jobs in London

Support ledger migration and data lake cleanup by extracting, transforming, reconciling and validating large datasets. Develop and validate SQL queries, batch jobs and processing logic, perform regression testing, document mappings and validation rules, and collaborate with engineering, product and business teams to ensure production readiness and post-migration validation.

The Data Solution Architect will lead multiple teams to design and deliver data solutions, manage employee performance, and contribute to technical design and pre-sales processes.

As a Senior Data Scientist, you'll develop AI solutions with machine learning, mentor others, and ensure responsible AI practices while collaborating with clients to solve business challenges.

Surgo Health seeks a Senior Product Manager for AI and Data Products to define product strategy, lead product initiatives, and collaborate with cross-functional teams. The role emphasizes building AI-driven solutions in healthcare and requires strong product management skills with a technical background.

The role involves client-facing responsibilities in technical configuration, data extraction, engineering, science, and deployment of analytics solutions, requiring effective communication and project management skills.

Lead data governance for the Chief Client Office: define governance frameworks, data ownership, quality, lineage, access, and compliance. Drive data literacy, stakeholder engagement, and AI enablement while partnering with enterprise teams to deliver fit-for-purpose data assets and measurable roadmaps.

Build and operate distributed ingestion and processing pipelines, ensure reliability and performance, define data contracts, add observability and testing, improve platform reliability and CI/CD, and participate in design/code reviews and incident retrospectives.

Support the Actuarial pricing team in data transformation projects, testing pricing models, data development, and analytics using various tools and technologies.

Manage and coach multiple sport-specific data science leads, ensure alignment and delivery of forecasting models, plan resourcing and staffing, maintain technical standards and cross-team collaboration, escalate and resolve technical or resourcing issues, and contribute to department strategy, tooling, and hiring.

Design, build, and maintain scalable data pipelines and storage for fraud detection. Support fraud analytics, feature engineering, model integration and serving, pipeline monitoring, and documentation. Collaborate with data, product, and engineering teams to enable detection, reporting, and operationalisation of fraud models.

Senior leadership role to define and commercialise Data & Analytics capability, shape go-to-market for Data/AI, drive revenue and client growth, build and lead a multidisciplinary data organisation, ensure delivery excellence, governance and reusable assets across regulated sectors using Microsoft data technologies.

Build and maintain large-scale data pipelines and distributed systems to ingest, process, store, and serve petabytes of vehicle data for ML and AD/ADAS development. Collaborate with ML and CV engineers, design cloud-native solutions, and ensure reliability, observability, and automation across data platforms.

Lead design, implementation, and operation of enterprise-scale international data platforms. Build and mentor global data engineering teams, define architecture and governance, ensure scalability, reliability, security, and cost optimization, and partner with analytics and business stakeholders to deliver data solutions and demonstrate ROI.

The Product Manager for Data will lead the rollout of data products for clients, overseeing requirements, development support, adoption, and communication while contributing to a global data model.

Lead research and prototyping of transformer-based models for retail challenges, design novel architectures, build research-grade prototypes, support productionisation, mentor data scientists, and partner with engineering, product, and academic collaborators to embed generative, multimodal, and representation-learning advances into scalable solutions.

Own the end-to-end product lifecycle for Sustainable Investment (SI) data platforms: define roadmap; onboard and operationalize new data sources; lead migration from legacy systems to cloud/lakehouse/warehouse platforms; partner with engineering, operations, and commercial teams; and drive data quality, coverage, timeliness, and regulatory/client compliance.

Design, build, and operate scalable, reliable data lake and catalog services. Lead technical design, mentor engineers, promote observability/SLOs, and collaborate cross-functionally to deliver production-grade data platform capabilities.

Lead day-to-day management and operational delivery of strategic partner relationships (Meta, Google, TikTok, Amazon, ITV, Sky). Support joint business plans, coordinate governance, track commitments, align partner activity with WPP priorities, and enable agencies and clients to extract partner value. Help manage data and technology partner ecosystem, support implementation, procurement coordination, and cross-functional stakeholder alignment while driving operational improvements and team leadership.

Lead DBA/BI engineer ensuring availability and performance of SQL databases, data models and Power BI reports using SQL Server, SSAS, SSIS and Fabric. Provide around-the-clock support, maintain the finance system (GMS), centralise datasets, build/maintain analytics pipelines, liaise with vendors and IT teams, and drive technical improvements.

Lead investigation and resolution of broker margin data discrepancies by validating Python pipeline outputs against internal sources. Debug raw broker files, document margin calculation logic across account types, work with Data Engineering to translate business rules into Python, escalate structural data gaps, liaise with brokers and SMEs, and maintain mapping and audit documentation.

Lead delivery of the FCA's redress data strategy by analysing complaints and redress data, producing evidence-based insights, improving data governance and catalogues, supporting complaints reporting reforms, and engaging stakeholders including FOS and FSCS to strengthen consumer protection.

Develop and evaluate machine learning models linking DNA sequence and genetic variation to molecular phenotypes and disease. Build sequence-to-function models (variant effect and regulatory activity prediction), integrate sequence representations with transcriptomic and epigenomic data, collaborate with experimental teams to validate hypotheses, communicate results, and contribute to publications and documentation.

Build predictive models and statistical analyses using alternative and traditional market data, produce reproducible Python/SQL workflows, conduct research, collaborate with investment teams to generate actionable insights, communicate findings to non-technical stakeholders, and support data engineering and best-practice development.

Lead platform product strategy and delivery for an AI-native data automation platform. Drive migration of legacy capabilities, define and build AI/ML platform features, manage prioritisation and internal service model, coordinate cross-functional teams, and grow a high-performing product organisation to support regulated financial services use cases.

Build and evolve a data and ML platform: implement IaC and CI/CD, develop Python/Spark components, support data/ML lifecycle and AgentOps, enforce security and observability, and collaborate with engineers and scientists to enable platform adoption.