Top Data Science Jobs in London

Off-cycle quantitative research intern supporting systematic trading, financial engineering, statistical modeling, portfolio optimization, and derivatives pricing. Responsibilities include developing mathematical models and algorithms, valuing and hedging transactions, conducting alpha research, calibrating models, optimizing pricing, managing portfolio risk, and collaborating with traders, technologists, sales, and risk teams. Candidates gain hands-on global markets experience and may be considered for full-time employment after successful completion.

Nine-week Global Markets summer internship supporting research, market monitoring, trade idea development, portfolio reviews, and financial solution analysis. Interns join Trading, Structuring and Origination, Systematic Trading, or Digital Markets tracks, gaining hands-on experience, technical training, networking, and exposure to risk management, derivatives, systematic strategies, automation, and digital market solutions.

Lead and scale a global HR Analytics Advisor team that partners with executives and HR leaders to turn workforce data into actionable decisions. Responsibilities include proactive and ad hoc analytics, executive storytelling, workforce risk and talent insights, HR process integration, self-service reporting, predictive modeling, data governance, and defining advisory operating models and success metrics.

Conduct quantitative research for systematic trading and financial markets. Develop mathematical models, algorithms, and infrastructure to price, hedge, and trade financial products. Perform alpha research, model calibration, portfolio optimization, and risk management while collaborating with traders, technologists, sales, marketing, and risk teams. Translate research into trading applications and communicate findings clearly. The program includes hands-on training and may lead to full-time employment.

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 the Verification Data Science team supporting KYC onboarding and document verification. Owns the data science roadmap, guides machine learning projects, manages image and tabular datasets, develops deep learning models, optimizes production performance, and maintains Python systems. Coaches and develops data scientists, collaborates with cross-functional stakeholders, communicates technical impact, and researches methods to improve verification and prevent criminal activity.

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.

As a Senior Machine Learning Engineer, you will develop ultra-realistic simulations for autonomous vehicles using foundation models, collaborate with teams, design experiments, and integrate models into applications.

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.

Leads the strategy, people, technical direction, governance, and delivery of data science, analytics, and AI capabilities supporting pharmaceutical R&D portfolio investment and resource-management decisions. Builds and develops multidisciplinary teams, delivers production-grade analytics applications, partners with senior stakeholders, establishes standards and data-quality practices, and promotes responsible AI in a regulated environment.

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 business analysis for global PlayStation Store and PlayStation Direct initiatives. Translates complex commercial needs into testable requirements, aligns senior stakeholders and cross-functional delivery teams, redesigns business processes, evaluates strategic trade-offs, and supports data-informed decisions. Partners with Product, Engineering, Analytics, Data Science, and Finance to deliver scalable commerce solutions while mentoring practitioners and improving business-analysis standards.

Technical Business Analyst supporting a data-focused client project in Bristol. Responsibilities include gathering and documenting business and technical requirements, analyzing data, translating business needs into technical specifications, identifying data processes, facilitating stakeholder discussions, and supporting delivery teams throughout the project lifecycle. The role requires onsite work three days per week and is an Outside IR35 contract running until 18th December, with potential extension.

Leads Intrum’s UK Investment & Analytics function, overseeing portfolio acquisition strategy, valuation, pricing, underwriting, performance optimization, advanced analytics, forecasting, and investment governance. Advises executive leadership and investment committees on opportunities, risks, capital allocation, and market trends. Ensures regulatory compliance, risk management, and disciplined investment decisions while building high-performing analytical and commercial teams.

Graduate trainee role developing data science expertise through a 12-month programme. Responsibilities include applying statistical analysis, machine learning, AI, data visualization, and generative AI to complex business problems; building, deploying, monitoring, and improving models using cloud technology; analyzing large datasets; collaborating with engineers and analysts; and applying responsible AI and data privacy principles.

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 HS2’s Data Intelligence function, overseeing data governance, Microsoft Fabric, reporting, predictive analytics, benchmarking, and performance assurance. The role transforms complex project controls, cost, commercial, schedule, risk, and performance data into actionable insights for senior decision-making. It requires leadership of data analysis and project controls teams, advanced Power BI, Power Query, DAX, Excel, predictive modelling, and experience delivering intelligence products within major infrastructure projects.

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.

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 strategic R&D engagements from presales through delivery, translating scientific and business challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Builds trusted relationships with R&D executives, scientists, engineers, and technical teams; assesses data, compute, feasibility, value, staffing, and delivery plans. Develops reusable architectures and playbooks, oversees technical workstreams, evaluates emerging AI capabilities, and provides feedback to shape Microsoft Discovery products and scalable industry solutions.

Manages Data Science Leads across multiple sports modeling teams, ensuring consistent technical standards, delivery quality, resource planning, and team development. The role supports forecasting model delivery, hiring, performance management, cross-functional planning, capacity management, and department-wide strategy. It also serves as an escalation point for technical and resourcing challenges while fostering collaboration, innovation, and knowledge sharing across the data science organization.

Develops Gartner research and thought leadership on the economic impact of AI and technology disruption. Synthesizes economic analysis, quantitative evidence, financial statements, market intelligence, and business context into executive-level insights. Advises clients, presents at conferences and media engagements, supports business development, reviews research, and collaborates with modeling, data science, and data engineering teams. The role also contributes to research strategy, mentors colleagues, and builds authority in technology market economics.

Own the strategy, roadmap, backlog, and outcomes for AI-powered consumer financial experiences. Translate emerging AI capabilities into trusted, explainable products while partnering with design, engineering, data science, compliance, and go-to-market teams. Lead discovery, delivery, iteration, prioritization, documentation, and customer-informed improvements in a rapidly changing technology environment.