Top Data Jobs in London

Lead AI, data science, and data engineering across Europe & RoW fleet business to define AI and data strategy, build scalable data platforms, deliver end-to-end AI initiatives with measurable business impact, drive adoption, and lead a multidisciplinary team while partnering with commercial and operational stakeholders.

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.

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.

Design, build, and optimise cloud-based data pipelines, ETL/ELT processes and enterprise data platforms for an insurance client. Integrate multiple source systems, ensure data quality and performance, support data modelling and transformation, and collaborate with stakeholders using Agile practices.

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 Data Engineer will build data pipelines for materials science, ensuring data quality and collaborating with ML researchers while managing large datasets.

Operate and monitor live sports trading systems, execute trades to meet performance targets, identify market inefficiencies, provide real-time feedback to developers and quants, troubleshoot issues, and help optimise the trading pipeline across shifts.

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.

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.

As a Senior Credit Risk Data Scientist, you'll lead credit risk modeling, develop data-driven lending strategies, and ensure statistical rigor in model performance while writing production-grade code for underwriting systems.

As a Principal Applied Data Scientist, lead the development of scalable AI solutions, focusing on NLP and LLMs, while collaborating with teams and ensuring production standards.

Lead design and implementation of secure, scalable cloud data architectures; drive adoption of AWS/Azure/GCP services; collaborate with data engineers to deliver data for analytics; assess data management technologies, promote data governance, mentor staff, and articulate architectural trade-offs to improve data quality and delivery supporting business roadmaps.

Deliver and migrate production ML data pipelines from Databricks to an AWS SageMaker MLOps platform. Build feature engineering pipelines and feature store integrations, ensure parity/testing with Databricks outputs, manage storage/permissions/IAM, deploy via CI/CD and IaC, document runbooks, and collaborate with engineering, AWS ProServe, and client teams in a regulated iGaming environment.

Lead the design, development, and operation of analytical and ML systems for financial services, ensuring model accuracy and compliance.

Lead data, technology, and AI strategy for a major global client: advise CMOs, define first-party data strategy, implement cloud/martech/adtech/analytics solutions, design measurement and optimization frameworks, assemble and manage a global data and tech team, and build client capability through education and change management.

The Staff Backend Engineer will lead the technical vision for Depop's data platform, focusing on data ingestion, scalability, observability, and architecting data solutions while mentoring team members.

Design, build, and maintain production data pipelines and warehouse/lakehouse architecture. Implement version-controlled transformations (dbt), orchestration, IaC, monitoring, and data quality. Enable secure, auditable data access for analysts and product teams, and define long-term platform strategy while partnering across engineering, analytics, and product.

Design and develop scalable reference-data services, automate lifecycle events, build/internal and external reporting (real-time and batch), collaborate with research and execution teams, maintain CI/CD and automated testing, and integrate Python and C# components to support trading and research workflows.

Develop scalable cloud-native platforms for real-time tick data. Collaborate with researchers, architect systems, and build distributed data architectures.

Drive enterprise sales for Quadient by executing territory plans, prospecting and building pipeline via direct and partner channels, presenting value-based proposals, responding to RFPs, using Salesforce for forecasting, engaging internal teams, negotiating contracts, and positioning Quadient Professional Services and product solutions (CCM/CXM, SaaS/Cloud) to meet quota.

Design, develop, and optimize enterprise-scale Snowflake data warehouses, pipelines, models, queries, and workflows. Build ingestion and transformation processes with Python, PySpark, Airflow, and AWS. Ensure data quality, governance, security, compliance, performance, and cost efficiency. Automate deployment and monitoring through CI/CD and DevOps practices, troubleshoot production issues, and collaborate with stakeholders and engineering teams. Provide technical leadership, lead discussions, and mentor engineers.

Lead development of reserving analytics by building dashboards, datasets, and self-service tools to surface trends and drivers. Partner with Reserving, Actuarial, Finance, Claims, Underwriting, and Data & Analytics to improve data quality, reduce manual work, promote responsible AI use, and present clear visualizations and governed metrics to support reserving decisions and senior stakeholders.

Support the end-to-end analytics stack: respond to data requests, contribute to dbt models/tests/docs, build BI dashboards in Hex, automate regulatory reporting, operate and govern data tools, assist migrations and ad-hoc investigations, and drive data quality and governance across the business.

Design, develop and automate data pipelines ingesting transactional, social and geographic data. Build crawlers and APIs, develop algorithms and statistical models (including clustering) for large-scale graph data, and improve infrastructure and internal tools.

Serve as a hybrid Technical Product Owner/Business Analyst for equity index calculation and data within the T3 platform. Drive roadmap prioritization, translate requirements into ADO epics/stories, manage backlog, support agile ceremonies and UAT, assess legacy data processes, identify automation opportunities, and collaborate across index management, R&D, operations, technology, and data teams to improve data quality and platform scalability.