Top Data Science Jobs in London

Leads Wise’s global Servicing Scale organization, covering workforce management, demand and performance management, capacity planning, and internal tooling. Owns operational planning automation, technical standards, global budget and headcount, outsourcing strategy, and product roadmaps for workforce and capacity systems. Builds scalable, data-driven infrastructure using AI and predictive modeling while developing senior leaders, influencing executives, and ensuring servicing operations can support rapid customer growth without proportional cost increases.

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.

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.

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.

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.

Manage the EMEA Security Operations Center within a global 24/7 operation. Responsibilities include defining processes, workflows, and playbooks; maintaining shift coverage and quality assurance; coaching analysts; developing training; partnering with Product, Support, and security teams; improving incident response capabilities; tracking objectives and key results; operationalizing new services; and representing the company in public speaking engagements.

Leads the global Clinical Operations AI portfolio, overseeing planning, delivery, reporting, governance, risk management, roadmap alignment, adoption, change management, training, and benefits realization. Partners with clinical, technical, data, compliance, and business stakeholders to deploy scalable, compliant AI solutions and drive measurable transformation across clinical operations.

Own and operate production Python infrastructure for FX pricing, risk, and trading systems. Responsibilities include developing microservices, shared quantitative libraries, monitoring and alerting, CI/CD, deployment, incident response, and root-cause analysis. The role also offers growth into curve construction, pricing models, trading strategies, risk modeling, backtesting, and customer behavior modeling while collaborating with quants, traders, analysts, product managers, and engineers.

Leads automation strategy for global VAT compliance and reporting. Identifies process inefficiencies, translates VAT requirements into technical solutions, manages automation projects through implementation, and supports ongoing process improvements. Works with clients, VAT teams, delivery groups, and technology teams while applying analytics, data science, AI, workflow automation, and emerging technologies. Also coaches team members, manages delivery risks, ensures data integrity and controls, and prioritizes initiatives independently.

Provides technical consulting across architecture, engineering, software, telecommunications, cybersecurity, and data disciplines. Translates operational requirements into secure, scalable, interoperable solutions; develops technical designs and documentation; supports integration, testing, transition, and operations; assesses risks and technical trade-offs; and contributes to governance, assurance, and lifecycle activities in complex, secure public-sector environments.

Lead enterprise architecture consulting engagements by aligning technology strategy with business goals, developing architecture frameworks, capability models, operating models, and transformation roadmaps. Advise senior client stakeholders, support sales and proposals, govern solution delivery, mentor teams, and build internal architecture methodologies and offerings. The role spans business, data, application, technology, infrastructure, cloud, emerging technologies, security, and enterprise transformation.

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.

Lead product strategy for payments optimisation, collaborate with engineering and data teams, drive commercial success, and deliver high-impact products.

Analyze short-term wholesale power markets, support price forecasting and trading strategies, monitor EDF portfolio optimization, and communicate time-critical risk information. Develop and maintain optimization models, data science applications, automated workflows, visualizations, and web tools. Improve application robustness through testing and refactoring, participate in peer reviews, train junior analysts, and collaborate with traders, asset managers, and international analytical teams while ensuring REMIT compliance.

Partner with senior Data leaders to develop talent acquisition strategies and recruit Data Scientists, Data Engineers, and Bioinformaticians. Source passive candidates, manage pipelines and interview processes, provide hiring-market insights, improve recruitment processes, use data to measure outcomes, and deliver excellent candidate experiences. The role also supports employer branding, events, interview training, reporting, and inclusive hiring practices in a hybrid London environment.

Lead the AML Risk data science team and develop machine learning, GenAI, and statistical solutions for global anti-money laundering detection. Build supervised and unsupervised detection controls, evaluate and optimize model performance, create investigator insights, improve operational processes, and deploy production-grade Python services and automated retraining pipelines. Responsibilities also include hiring, mentoring, cross-functional collaboration, and managing projects that improve model training and financial crime detection.

Lead the strategy and growth of the Data Practice at Capco, managing multidisciplinary teams and delivering high-impact analytics projects in Financial Services.

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 the development of AI-enabled products within a consulting environment focused on financial services and energy, utilizing modern AI tools and methodologies.

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.

Develop and improve data science and machine learning models for marketing and consumer insights, including attribution, personalization, forecasting, experimentation, and marketing measurement. Prepare datasets, define evaluation metrics, support model deployment, and generate insights from media, pricing, promotions, and syndicated data. Collaborate with product owners, data engineers, and machine learning engineers; contribute to responsible AI governance, code reviews, reusable AI assets, and mentorship of junior team members.

Develop, implement, and deploy statistical and machine learning sports models and pricing engines in Python; engineer sports data assets; build automated tests; collaborate with Trading, Product, Engineering, and QA; validate data flows and integrations; and mentor junior data scientists.

As a Senior Data Science Engineer, you'll lead data science projects, develop algorithms, analyze datasets, and mentor junior team members to enhance trading operations and strategies.

Lead and develop a Data Science team to deliver scalable ML/AI solutions for an online Personalisation programme, ensuring impactful customer experiences.

Serve as a pre-sales technical advisor for enterprise customers, translating business needs into scalable LLM architectures using Claude. Lead technical discovery, develop evaluations, design integrations with enterprise systems, create tailored technical content, and coordinate across Sales, Product, and Engineering to drive deployments and adoption. Provide occasional on-site workshops and maintain expertise in LLM capabilities and implementation patterns.