Top Data Jobs in London

Lead and own LoopMe's AI throttling system and related AI products end-to-end. Manage a team of four data scientists/ML engineers, define roadmap, partner with commercial and operations teams, deploy and monitor production models, measure causal business impact, and maintain technical quality across modelling and systems.

Deliver advanced analytics, dashboards, and predictive insights using BI and AI to support decision-making. Establish data governance, design data lakes/marts, standardise visualisation, enable federated self-service, and improve data quality and reporting across the bank.

Design, build, and maintain scalable Snowflake-based data platforms and pipelines using Python. Deliver secure, high-quality data for reporting, analytics, regulatory needs, and predictive/ML forecasting. Partner with stakeholders and Power BI developers, enforce data governance, and improve processes through automation and AI.

Build and maintain automated data collection pipelines, clean and model Gas and LNG datasets, produce analyses and visualisations to support trading, collaborate with data scientists and traders, and deploy/operate data products with strong data governance.

Build and maintain scalable ETL/ELT pipelines, integrate ServiceNow and Salesforce data, implement Microsoft Fabric medallion architecture, and develop Power BI reports and semantic models to deliver reliable insights and support stakeholders.

Apply advanced data science, machine learning and Gen-AI to build AI-native products, perform technology due diligence, competitive intelligence, forecasting, and benchmarking. Develop analytics frameworks, KPIs, visualizations, and collaborate with Technology and AI teams to prototype AI/ML solutions and automate market and technology insights for strategic decision-making.

Lead product strategy and roadmap for Finance Technology, driving AI/ML and data initiatives. Own backlog, stakeholder alignment, business process redesign, data modeling, lineage, and governance. Build business cases, prioritize delivery in agile teams, and ensure security, compliance, and AI safety while improving operational efficiency and user experience across finance systems.

Lead end-to-end data science and AI initiatives: design and deploy ML models, implement MLOps pipelines, perform advanced modeling and analysis, ensure ethical AI, mentor junior staff, and collaborate with stakeholders to translate requirements and shape strategy.

Perform data profiling and analysis, build and maintain visualisations and dashboards, define KPIs and a performance management framework, present actionable insights, lead stakeholder workshops, and collaborate with agile delivery teams to support decision-making.

Define and document analytics requirements and tracking designs, write implementation-ready Jira stories, support client- and server-side tracking across web and app, validate implementations, maintain tracking governance, perform audits and root-cause analysis, and keep comprehensive documentation of event taxonomies, validation processes, and measurement best practices.

Define and document measurement requirements, design tracking specifications, and implement/validate client- and server-side tracking across web and app. Maintain governance, audit event taxonomies, troubleshoot data quality issues, and collaborate with Product, Engineering, and Analytics to enable attribution, experimentation, personalisation, and insight-driven decisions.

Design, develop, and optimize high-performance data pipelines and workflows on Databricks and AWS. Support L2/L3 production pipeline troubleshooting, implement monitoring and CI/CD deployment, and ensure data quality, security, and compliance. Collaborate with architects and analysts to build data models and performance-tuned transformations.

Design, build and automate scalable data models, pipelines and tooling using Python and SQL to support BPA onboarding and administration. Analyse and transform DB pensions data, perform mapping and migrations, implement validation, reconciliation and governance, and collaborate with actuarial, operations and transformation teams to embed best practice and support strategic data programmes.

Design and deliver analytical solutions supporting property insight, estate rotation and modernisation. Translate senior stakeholder needs into analyses, models, MI and controls. Build descriptive and predictive models, create visual narratives and present insights to senior audiences. Provide guidance to analyst colleagues and share best practices across the organisation.

Support global markets by building and maintaining scalable data pipelines and datasets, partnering with traders and quants, improving data infrastructure and governance, diagnosing analytics issues, and translating technical outputs into clear insights for non-technical stakeholders.

Lead causal and economic analysis of player value, build offline policy-evaluation and simulation tooling, guide model development, and translate causal insights into commercial decisions. Mentor peers, implement production-ready models, and communicate findings to technical and commercial stakeholders.

Lead technical delivery of cloud-native data and analytics products. Design and implement secure, scalable solutions, champion CI/CD and IaC, embed governance, mentor engineers, and collaborate with stakeholders to drive analytics platform strategy and operational excellence.

Design, build, and operate governed data pipelines and context layers for AI agents integrating Salesforce, SAP, and service data. Implement feedback loops, data-quality frameworks, semantic models, Power BI reporting, and secure API-based integrations to support enterprise commercial AI workflows.

Design and deliver data products by analyzing large datasets, building data pipelines and predictive ML models, integrating AI into business functionality, and deploying solutions to client platforms. Collaborate with stakeholders and engineers to translate requirements into production-ready data products and communicate results to technical and non-technical audiences.

Lead growth-focused data science initiatives, owning LTV prediction models across countries and channels. Translate business questions into models, analyze large customer and marketing datasets, evaluate acquisition quality, monitor and productionise models with engineering partners, and drive data-informed growth and retention decisions.

Lead cost management for data centre projects including feasibility, estimating, tendering, post-contract cost control, valuations, monthly reporting, value engineering, final accounts, client/consultant liaison, team leadership and continuous improvement of cost management processes.

Lead cost management for large-scale, complex data centre projects. Manage budgets, procurement approaches and contract forms; maintain industry supply-chain relationships and ensure compliance with European design and code requirements. Drive commercial growth (Associate Director responsibility: deliver >20% annual growth) and collaborate with country P&L owners to align sector ambitions with business operations.

Lead cost estimation and financial planning for data centre projects, developing detailed estimating models across building, infrastructure, MEP, power and specialist systems. Produce cost plans, benchmarks and risk/opportunity analyses, support investment decisions and capital approvals, and monitor market trends affecting labour, materials and supply chains. Ensure accuracy and quality of estimating deliverables across all design stages.

Manage cost planning and control for data centre projects: feasibility, tendering, post-contract valuations, change control, monthly reporting, value engineering, client/consultant liaison, team leadership, and bid support.

Lead MEP cost control for data centre projects including detailed estimates, cost variance analysis, tendering, procurement, value engineering, change management, cashflow forecasting, contract administration, compliance, and mentoring junior staff.