Top Data Jobs in London

The Data Science Manager will collaborate with business partners, oversee predictive model building, manage a team, and deliver analytical insights to drive business decisions.

As a Senior Data Scientist, you will optimize marketing performance, develop machine learning models, analyze A/B tests, and collaborate closely with marketing and data engineering teams.

The Senior Data Scientist will optimize marketing campaigns using data solutions, machine learning models, and collaboration with performance marketing teams to enhance business strategies at Preply.

Hands-on role ensuring completeness, quality, and accuracy of product data for multi-region launches. Perform data validation, stewardship, QA, syndication (PIM), reporting, and stakeholder coordination to resolve discrepancies and track launch readiness.

Design, build, test and document secure batch and real-time data pipelines, perform logical/physical database design and data modelling, expand platform capabilities, analyse and resolve data processing issues, and ensure alignment with data architecture for downstream consumers.

Build, test, and document secure batch and real-time data pipelines for a government client; design logical and physical databases; extend platform capabilities; ensure data models align with architecture; perform data analysis and root-cause investigations to improve processing and availability for downstream consumers.

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.

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.

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.

Designs and governs enterprise data architectures supporting analytics, reporting, operations, and AI initiatives. Responsibilities include data modeling, warehousing, integration pipelines, APIs, governance, quality, lineage, security, and architecture optimization. The role provides technical leadership and mentorship, guides cloud and big data technology decisions, develops proofs of concept and roadmaps, and supports client proposals and account growth. Collaboration with engineers, analysts, developers, and business stakeholders is central to delivering scalable, secure, high-performance data platforms.

Support development and continuous improvement of data products for electricity transmission network planning and operations. Define roadmaps, manage backlogs, gather requirements, validate data quality and lineage, collaborate with stakeholders and delivery teams, enable analytics and governance, and measure product performance and adoption.

Lead business discovery and requirements analysis for data, reporting and analytics initiatives. Define processes, KPIs, data models, lineage and governance. Collaborate with analytics, data architects and delivery teams to elicit, validate and prioritise requirements, support testing, adoption and continuous improvement while managing stakeholders and multiple concurrent initiatives.

Lead enterprise data governance by defining frameworks, policies, and operating models. Manage data quality, metadata, catalogs, lineage, stewardship, compliance, and MDM. Collaborate with stakeholders, run governance councils, track KPIs, and support analytics, cloud, and AI initiatives.

Develop, validate, and deploy machine learning and statistical models for soccer betting products. Create soccer-specific features, run offline and online experiments, collaborate with data engineering and product teams, follow software engineering best practices, document work, and present findings to technical and non-technical stakeholders.

Lead the data science organization to deliver AI products, mentoring teams and executing a strategic vision for machine learning applications.

As a Lead Data Engineer, you will design and develop software for data processing, lead a team, ensure quality, and manage technical proposals.

As a Senior Data Platform Engineer, you will design and operate a scalable data platform, support analytics, mentor junior engineers, and drive technical excellence.

The Principal Data Scientist will lead complex projects, drive innovation in AI solutions, mentor teams, and influence data science strategy.

As a kdb+ Developer, you'll work on trade surveillance projects, collaborating with business users, developing client applications, mentoring junior developers, and analyzing data to create client reports.

Lead cross-functional initiatives to enhance KOL data products, translating customer needs into development initiatives and ensuring data quality and usability.

Design, build and optimise ETL/ELT pipelines and data foundations across enterprise systems. Profile, cleanse, map and reconcile data, implement quality frameworks, develop scalable data models on cloud platforms, and work with stakeholders to establish repeatable data architecture, governance and reporting for transformation programmes.

Design, develop, and deploy scalable ML and time-series forecasting engines integrated into Anaplan applications. Lead customer onboarding and customize models to client data, build feature pipelines (SQL/Python/dbt), and operationalize models via MLOps tools (MLflow, Optuna). Collaborate with Product, Engineering, and Customer Success to deliver production-grade, monitored solutions.

Design and govern end-to-end data architectures and standards, guide technology selection, lead large data migrations to cloud-native platforms, enable real-time data services, mentor engineers, and ensure secure, scalable data solutions that support AI/ML workloads.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

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.