Top Data Jobs in London

Develop statistical models, machine learning solutions, and actionable insights using retail transaction, shopper, and clickstream data. Partner with clients and leadership teams to identify growth opportunities, build scalable analytical solutions, and deliver measurable commercial impact. The role requires translating complex technical concepts for non-technical stakeholders, creating new analytical workstreams, and mentoring others.

Develop and maintain Python ETL pipelines, including real-time workflows, data warehouses, Flask services, APIs, and Postgres databases. Support automated reporting, data exploration, and machine learning model training and deployment for user segmentation, anomaly detection, forecasting, and recommendations. Maintain data infrastructure across Redshift and BigQuery, deploy services to Kubernetes, and collaborate with teams using Agile practices.

Supports consulting data science projects by preparing and analyzing datasets, applying statistical and machine learning techniques, developing scalable models, creating visualizations, and communicating insights to clients. The role involves working with senior data scientists, contributing to agile client engagements, writing maintainable code, following ethical data practices, and developing expertise across cloud, on-premise, and hybrid environments.

Supports the design, testing, and delivery of data pipelines and architectures across cloud, on-premise, and hybrid environments. Responsibilities include ETL/ELT, data modelling, migration, data cleansing, stakeholder engagement, documentation, and client deliverables. The role is designed for graduates developing foundational data engineering, cloud, governance, and consulting skills while contributing to secure and ethical data solutions.

Designs and delivers secure, scalable data architectures across AWS and Azure. Responsibilities include automated ETL/ELT pipelines, event-driven processing, cloud and on-premises integration, performance optimization, self-service data ingestion, infrastructure as code, CI/CD, architecture documentation, and technical leadership. The role supports fraud detection and advanced analytics while collaborating with data, cloud, security, infrastructure, engineering, and business stakeholders in regulated Government and Defence environments.

Supports Finance Systems Data & Change projects by delivering regulatory and business reporting changes, improving processes, and enhancing efficiency across reporting platforms. The placement includes a 12-month social-impact project, data analysis, problem-solving, teamwork, and structured development within Nationwide’s Finance function.

The Assistant Professor will develop an internationally recognised research programme, publish impactful work, secure external funding, and build industry partnerships. Responsibilities include designing and delivering undergraduate and postgraduate teaching, curriculum development, student assessment, PhD supervision, mentoring, knowledge transfer, enterprise, outreach, and departmental administration. The role also involves contributing to equality, diversity, inclusion, strategic initiatives, and a supportive academic community.

Leads data governance, master data, and migration workstreams for large-scale SAP S/4HANA transformation programs. Advises executives on data strategy, governance models, organizational readiness, and data quality. Facilitates stakeholder workshops, develops transformation roadmaps, manages risks and dependencies, and drives alignment across complex organizations. Supports consulting pursuits, proposal development, solution shaping, and pre-sales activities.

Develop and maintain production data and machine learning platforms, APIs, pipelines, and services supporting live retail planning systems. Package, serve, version, and monitor machine learning models; improve CI/CD and deployment processes; define architectures and service boundaries; collaborate with data scientists and engineering teams; and provide on-call support for mission-critical tools.

Analyze and improve patent data quality across families, ownership, legal status, and coverage. Define quality standards, build test sets, investigate anomalies and root causes, assess new data sources, review AI-assisted enrichment, document rules, and lead quality-improvement projects. The role combines patent expertise with hands-on SQL and Python analysis, automated testing, stakeholder communication, and continuous improvement of AI-ready data.

Provides regional technical authority for BMS, EPMS, PLC, OT, and DCIM architectures across data centres. Defines engineering standards, governs complex designs, resolves high-impact technical risks, leads vendor and product strategies, and mentors engineering teams. Advises executives on technology roadmaps and ensures reliable, scalable mission-critical infrastructure.

Leads global downstream marketing for Medtronic’s AI- and data-enabled surgical technology portfolio. Develops commercial narratives, value propositions, launch strategies, campaigns, sales tools, and customer-facing content. Translates technical and clinical information into credible messaging, partners with product, clinical, regulatory, legal, privacy, and regional teams, and supports customer segmentation, thought leadership, congresses, and adoption measurement. The role drives consistent positioning and commercialization of Touch Surgery ecosystem capabilities across global markets.

Lead enterprise Salesforce Marketing Cloud and Data 360 architecture programs. Advise C-level stakeholders, define scalable engagement and data architectures, oversee integrations, governance, identity resolution, segmentation, activation, and privacy compliance. Lead workshops, technical design, testing, deployment, risk management, and code reviews while mentoring architects and guiding delivery teams. Translate business goals into technology roadmaps supporting Agentforce and AI-driven personalization.

Deliver client-facing enterprise data architecture consulting for AI-ready data estates. Assess data landscapes, design cloud, lakehouse, warehouse, semantic, governance, metadata, lineage, data product, knowledge graph, and GenAI retrieval architectures. Advise on platform trade-offs, data quality, security, provenance, and modernization roadmaps while translating technical decisions into business outcomes. Collaborate with data, AI, engineering, and business teams; contribute to proposals, thought leadership, and implementation planning. Travel may reach 60% across the UK and internationally.

Own complex data privacy operations across a global organization, including data mapping, Records of Processing Activities, DPIAs, privacy risk assessments, supplier reviews, data subject rights, retention, incidents, and assurance. Partner with legal, governance, technology, engineering, and business teams to translate privacy requirements into practical controls. Improve processes, reporting, automation, and privacy tooling while coaching colleagues and advising senior stakeholders.

Manage Lloyd’s Insights Hub and Data & AI Community, driving adoption, user satisfaction, data governance, product improvements, events, content, and Microsoft Copilot use cases. Build relationships across the organization and market, support Business Data Lab cohorts using Databricks, coordinate suppliers, and help analysts, data scientists, and actuaries turn ideas into valuable analytics solutions.

Analyze reader engagement and content performance to provide insights for newsroom strategy and business decisions. The role involves interpreting editorial and audience data, communicating findings to varied audiences, collaborating with Product and Engineering on features and experiments, and following data privacy and governance standards.

Own credit risk and Customer Lifetime Value modeling projects end to end, including research, production deployment, monitoring, and commercial impact. Set technical direction across multi-quarter initiatives, evaluate uncertainty and model calibration, improve existing models, and explore new machine learning approaches. Lead projects, communicate clearly, challenge assumptions with evidence, and use AI to accelerate prototyping and R&D.

Build, maintain, and improve probabilistic credit risk and customer lifetime value models for automated and human-assisted lending decisions. The role involves applied statistical research, causal estimation, model calibration, production machine learning, and evaluating new modeling approaches. The successful candidate will independently frame ambiguous analytical problems, communicate findings clearly, use AI effectively, and support credit, pricing, and portfolio strategy across UK and German lending markets.

Develop investment data strategies, pipelines, databases, and models integrating research and portfolio information. Build AI-enabled applications using LLMs, RAG, semantic search, vector databases, and agent frameworks. Create dashboards and tools for investment professionals, prototype solutions, collaborate with engineering and investment teams, and transition successful concepts into scalable applications.

Own the vision, roadmap, prioritization, backlog, and measurable outcomes for Client Platform data and analytics products. Translate business and user needs into governed, reusable capabilities supporting reporting, analytics, workflows, automation, and AI. Lead discovery, stakeholder alignment, delivery decisions, adoption, risk management, and cross-functional collaboration with engineering, design, data, operations, risk, compliance, and business teams in a regulated financial-services environment.

Leads end-to-end architecture for enterprise data platforms, data products, analytics, and AI-enabled solutions. Designs cloud-based data lakes, warehouses, lakehouses, integration frameworks, and analytics platforms; establishes governance standards and technology roadmaps; evaluates architectural options and risks; and provides technical leadership to engineering and delivery teams. The role partners with stakeholders to translate business needs into scalable, secure solutions and supports adoption of generative AI, agentic BI, and intelligent automation.

Lead the design and delivery of modern data and AI solutions for multiple customers. Provide architectural direction, technical assurance, and thought leadership while advising senior stakeholders on strategic and technical decisions. Manage and mentor architects and engineers, develop standards and account strategies, support agile teams, build customer relationships, and guide scalable, distributed, cloud-based applications. The role also involves business development, technology advocacy, and fostering inclusive, high-performing teams.

Develop and govern EMEA crisis and incident data landscapes, models, dashboards, and reporting. Produce management information, KPIs, KRIs, and resilience metrics for senior forums while ensuring data accuracy, auditability, and regulatory compliance. Support incident and crisis management teams, thematic reviews, maturity assessments, regulatory reporting, and integration with ServiceNow and critical event management platforms.

Leads assurance and delivery oversight across a cluster of transformation workstreams. Assesses programme health, manages dependencies and capacity, challenges sponsors and workstream leads, and intervenes to recover at-risk initiatives. Supports governance decisions, readiness, adoption, benefits realization, and transition to business as usual while providing evidence-based delivery updates to senior leadership.