Top Data Science Jobs in London

Lead a global team to build, maintain and improve detection logic across MXDR technologies (EDR, NDR, SIEM). Set strategy, manage senior detection engineers, collaborate with TI/DFIR/Red Team, ensure high-fidelity detections with low false positives, apply data science to improve detection and SOC efficiency, and provide transparent client coverage reporting.

The Senior Product Manager will lead the strategy and development of the discovery experience for Ten's services, leveraging AI and data analytics for personalization, while mentoring junior team members and collaborating with cross-functional teams.

The Senior Director of Business Development will drive Cytel's Large Pharma expansion by managing client relationships, executing sales strategies, and leading proposal development.

Senior pricing and analytics leader for Asset Servicing responsible for developing pricing frameworks, governance, and margin management. Translate analytics into commercial insights, collaborate with product teams on benchmarks and fee schedules, maintain KPIs, and modernize BAU with AI, data science, automation and MLOps. Lead stakeholders and drive accountability for business outcomes.

Work with account teams and partners to solve complex data problems, demonstrate Snowflake via demos and proofs-of-concept, design solutions, build technical champions, and represent Snowflake at events while collaborating with Product, Engineering, and partners to drive customer success and close deals.

Lead design and delivery of production-grade ML and GenAI solutions on the Databricks platform. Architect end-to-end ML pipelines, optimize training/inference, implement MLOps/LLMOps, build MVPs for sales, influence product roadmap, mentor peers, and present technical content externally.

Lead the development of reporting and analytics capabilities, improve product features, and drive cross-functional collaboration to enhance customer satisfaction and revenue growth.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Lead end-to-end design and delivery of a global claims transformation program, translating business needs into technical requirements, coordinating cross-functional teams to implement automation and AI solutions, managing project plans, budgets, risk, and change adoption across international claims operations.

The Account Manager, SSP Partnerships will manage client relationships in the SSP portfolio, focusing on revenue growth and collaboration with internal teams.

Lead and mentor data science teams to design, develop, and deploy ML and AI solutions (including GenAI/LLMs). Align technical outcomes with business goals, drive MLOps and model governance, and deliver scalable production systems.

Lead and manage a team of data scientists to design, build and deploy predictive sports models. Oversee algorithm development (probability, Monte Carlo, ML), mentor staff, collaborate with engineers and product managers, and ensure continuous delivery and high-performance, production-ready model implementations across multiple sports.

The Senior AI Transformation Consultant works with clients to identify AI opportunities, define robust business cases, and oversee AI project deployments, ensuring solutions deliver value.

Lead technical pre-sales efforts for UK accounts: present Snowflake to technical and executive audiences, build demos/POCs, develop technical champions, collaborate with sales, partners, product and engineering, and represent Snowflake at events to drive deal wins and implementations.

The role involves creating research content, providing insights in Analytics and AI, engaging with clients, and mentoring team members. A strong focus on industry trends and effective presentation skills is required.

Own and execute the roadmap for a core document verification product area, improve verification accuracy and conversion, partner with Engineering, AI/ML, Design, Growth and Ops, use analytics and experimentation to validate hypotheses, and prioritise investments while ensuring regulatory and compliance alignment.

Lead product strategy and roadmap for Equity and Multi‑Asset indices and an in‑house AI tool. Gather user feedback, prioritise features, work with research developers to ship, run market analysis, engage clients, and partner with Sales and Marketing to drive positioning and revenue.

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

Manage the applied methods Data Science team supporting autonomous driving. Set priorities and roadmaps, review technical designs, ensure statistical rigor, manage delivery, hire and develop data scientists, scale tooling and automation, and build strong relationships with Autonomy stakeholders and customers. The role requires causal inference expertise and experience leading high-performing teams, with desirable experience in ML, simulation, offline evaluation, distributed computing, and productionizing research.

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.

This role involves overseeing the product vision for IT & Cyber Risk, driving AI integration, collaborating on product delivery, and engaging with stakeholders to align product strategy with corporate goals.

Provide senior advisory and technical guidance for a foundational enterprise data program in financial services. Govern data mart modeling, schema and semantic-layer decisions; establish data science, reproducibility, documentation and data quality standards; assess analytical readiness; sequence remediation; advise on AI governance; and upskill FP&A and data engineering teams.

Design, build, and maintain end-to-end data ingestion pipelines and data architecture. Transition datasets to a new stack, map/standardize/normalize data, monitor data quality, manage vendor data inputs, and partner with commercial trading teams to gather requirements and support analytics and investing use cases.

Lead a data science team building always-on predictive models and pipelines for an AI platform. Own model lifecycle: production deployment, monitoring, drift detection, retraining, and measurable business outcomes. Provide technical leadership, code reviews, architecture decisions, and stakeholder collaboration. Hire and mentor data scientists, champion responsible and auditable AI, and adopt ML platform tooling (MLflow, model registries, Databricks) and LLM/RAG approaches where appropriate.

Lead and grow a team of data scientists focused on merchant acquisition, onboarding, order management, retention and self-serve tools. Define analytical direction, prioritise high-impact problems, drive experimentation, causal inference and applied ML work, partner with Product/Engineering/Commercial stakeholders, and translate analyses into product, operational and commercial decisions.