Top Data Science Jobs in London

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.

Deliver AI and productivity workshops, drop-in sessions, and technical learning content for apprentices. Facilitate engaging online sessions, moderate assignments, provide developmental feedback, coordinate learner interventions, and collaborate with coaches and operations teams. Apply AI in business contexts to explain technical concepts, support learner progress, and demonstrate how AI creates measurable business value. Maintain current industry knowledge and contribute to an inclusive, motivating learning environment.

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

Leads Expedia B2B’s analytics organization, managing analytics managers and senior analysts while shaping multi-year analytics roadmaps and business strategy. Partners with senior stakeholders to drive measurable outcomes, guides statistical and machine learning applications, establishes analytics engineering and visualization practices, develops talent, and collaborates with data engineering, product, and machine learning teams on scalable solutions.

Leads VGW’s global CRM and Live Operations function, owning player lifecycle strategy across acquisition, onboarding, engagement, retention, reactivation, loyalty, and monetization. Builds an integrated player engagement ecosystem, uses data science and analytics to optimize live events and channels, partners with Product, Data Science, Brand GMs, and FP&A, and manages global teams. Ensures commercial strategies support responsible gaming, compliance, risk mandates, player trust, and sustainable revenue growth.

Leads cross-functional programs from planning through execution, governance, adoption, and value realization. Manages roadmaps, milestones, risks, documentation, metrics, and executive reporting while coordinating technical, operational, and business stakeholders. Designs change-management and adoption strategies, conducts impact assessments, addresses resistance, and develops communication plans to embed solutions into business operations. Experience in data science, advanced analytics, or AI/ML initiatives is valued.

Leads enterprise data strategy, analytics, business intelligence, data science, experimentation, and game economy optimization. Builds trusted data platforms, governance, metrics, and decision frameworks while driving predictive analytics and responsible AI. Oversees monetization, segmentation, pricing, and portfolio-wide game economy standards to improve player engagement, retention, lifetime value, and commercial performance. Manages distributed technical and commercial teams and partners with Product and Live Operations leadership.

Lead cross-functional Risk initiatives from strategy through delivery and adoption. Define product and technical direction for risk infrastructure, data, AI, APIs, and user experiences; partner with engineering, data science, ML, and executive leaders; make investment decisions; resolve complex tradeoffs; influence without authority; mentor PMs; and advance product management practices across Stripe.

Lead the transformation of legacy products into a unified enterprise platform. Translate strategy into roadmaps, manage backlogs, prioritize cross-functional initiatives, and coordinate Engineering, UX, AI, Data Science, Commercial, and Operations teams. Drive platform discovery, delivery, launch, adoption, and measurable business outcomes. Integrate trustworthy AI and data capabilities into customer-facing workflows while influencing senior stakeholders and balancing customer value, commercial goals, technical feasibility, risk, and resources.

Owns net-new enterprise customer acquisition across a defined UK territory. Responsibilities include prospecting, developing, and closing complex SaaS and technical solution sales; presenting Snowflake’s AI Data Cloud, Cortex AI, Snowpark, and data ecosystem; conducting discovery and customized demos; advising C-level and technical stakeholders; managing partners; achieving sales quotas; and collaborating with sales engineering, marketing, legal, finance, and professional services.

Lead the research, development, testing, deployment, and maintenance of complex machine learning and generative AI models. Design MLOps pipelines for CI/CD, monitoring, retraining, and production operations. Solve complex technical problems, evaluate emerging AI technologies, deliver high-risk prototypes, integrate models with existing systems, and ensure model safety, security, performance, and reliability. Mentor junior team members and provide specialist generative AI expertise for public sector and national security projects.

Manage workstreams for bespoke AI transformation projects with pharmaceutical and life sciences clients. Responsibilities include understanding stakeholder needs, conducting open-source analysis, translating operational requirements into user stories, designing and testing workflows, collaborating with engineering teams, and contributing to thought leadership. The role requires prior technical transformation consulting experience, life sciences exposure, client relationship skills, analytical communication, and familiarity with Agile and iterative delivery.

Lead data science for Wise’s AML Risk team by developing machine-learning and GenAI detection systems, optimizing precision-recall tradeoffs, building coverage frameworks, and deploying production Python services. Hire and mentor specialists, collaborate with product, engineering, and operations teams, design model evaluation experiments, improve operational processes, and create investigator insights for detecting financial crime across global transactions.

Leads Supercell’s Marketing Data Science team, owning marketing measurement, predictive modeling, causal inference, and AI initiatives across mobile game marketing. The role combines project and stakeholder leadership, hands-on technical oversight, team management, hiring, and strategic direction. Responsibilities include attribution, pLTV, incrementality, media mix modeling, brand lift, audience modeling, productionization, and supporting game-team investment decisions. The position is based in Helsinki or London with significant time expected at Helsinki headquarters.

Lead technical direction and delivery of large-scale AI/ML platforms. Architect microservices and shared libraries, align ML, data science and DevOps, coach distributed engineers, define production readiness, and drive hiring and standards across software engineering.

Leads client data and AI engagements across industries, translating business challenges into analytics and technology solutions. Manages complex projects, client relationships, delivery teams, stakeholder alignment, and business development. Partners with engineers and data scientists to deploy and scale analytics, develops executive-facing insights, shapes operating models, and grows consulting capabilities in data and analytics.

Develop and operate quantitative models and production systems for FX pricing, risk management, forecasting, hedging, and trading. Build Python-based quant libraries, services, data pipelines, and monitoring systems; conduct validation and backtesting; manage deployments and incident response; and collaborate with quants, traders, analysts, product managers, engineers, and risk teams.

Own the strategy, roadmap, delivery, quality, governance, commercialization, and adoption of Cognism’s B2B data products. Translate customer needs into data requirements, collaborate with engineering and data science, evaluate ML-driven data features, define success metrics, manage cross-functional stakeholders, and ensure compliance, reliability, and customer value across APIs, CRMs, and agentic systems.

Own Beamery’s Data Foundry vision, strategy, roadmap, and commercial model. Define platform capabilities, data contracts, APIs, MCP access, governance, security, and privacy standards. Partner with product, data science, data engineering, integrations, sales, and customer success teams to prioritize delivery, validate customer needs, establish go-to-market plans, and measure business and customer value. Lead development of trusted, explainable AI and data products for enterprise workforce and talent use cases.

Leads a global AI and data science organization focused on workforce analytics. Sets technical strategy, directs research from hypothesis through production, develops model and evaluation factories, advances responsible agentic AI, and translates models into business and employee insights. Partners with technology teams on scalable platforms, prioritizes investments, communicates with senior leaders, and ensures compliance in a regulated enterprise environment.

Leads data science initiatives from conception through deployment, developing statistical models and machine learning algorithms for trading intelligence. Collaborates with cross-functional teams to productionize solutions, supports data-driven trading strategies, and contributes to trading automation design, development, maintenance, and testing. Communicates insights to stakeholders, mentors junior data scientists, and helps solve complex business problems using large datasets.

Define, architect, and lead delivery of machine learning and AI solutions. Support exploratory data analysis, proofs of concept, and the end-to-end data science lifecycle. Translate business problems into analytical and modeling solutions, communicate findings to technical and non-technical stakeholders, and provide specialist model delivery support. Design, develop, test, implement, and monitor models while tracking advances in data science and advising leadership on competitive capabilities.

Manages Leads across multiple sports data science teams, aligning forecasting model delivery, technical standards, resource planning, hiring, and team development. Partners with engineering and delivery leaders to address capacity, performance, and technical challenges while shaping data science strategy, tooling, and roadmaps. Requires advanced programming, sports modeling or betting expertise, leadership experience, and familiarity with model deployment and cross-functional planning.

Lead Quantium’s UK Growth practice by opening new industries, building client pipeline, activating cloud and AI partnerships, and scaling the AI Executive Edge program. The role involves selling AI transformation work, developing executive relationships, creating partnership-led opportunities, and collaborating with delivery teams to ensure client value. This is a first-on-the-ground position with significant responsibility for establishing Quantium’s market presence and growth approach in the UK.

Leads the global Data Science Center of Excellence, overseeing statistical modeling, econometrics, machine learning, AI, forecasting, attribution, experimentation, and optimization. Builds technical capability, mentors teams, establishes quality and governance standards, owns advanced analytics products and services, and drives innovation. Partners with technology, consulting, and client teams to translate complex data science into scalable solutions, commercial value, and measurable media and marketing outcomes.