Top Data Science Jobs in London

As a Data Science Managing Consultant, you will lead business development, manage teams, and deliver data-driven solutions in the transport sector, while coaching junior staff and contributing to thought leadership.

The Account Executive is responsible for managing the sales cycle, building relationships with clients, collaborating with engineering, and representing the company at events.

10-week on-site Data Science internship in London supporting data discovery, enrichment and analysis for quantitative research. Tasks include data blending, statistical analysis, exploratory data analysis, visualization, building tooling, and collaborating with data scientists to scale and automate data processes.

The Director of Colleague Data Science & Analytics will lead the global HR analytics function, driving innovative solutions to support decision-making and enhance the colleague experience.

Design and deliver statistical, probabilistic and simulation models to support decision-making. Translate business questions into deployable analytical solutions, quantify uncertainty, validate and monitor models, and partner with engineering, product and business teams to productionise models and define operational requirements.

Summer internship on the Global Data Science team to develop and optimize time-series forecasting models (ARIMA/SARIMA, XGBoost, LSTM). Support end-to-end data ingestion, back-test datasets, collaborate with traders and analysts, and conduct ad hoc research on energy fundamentals and analytics trends.

Lead commercial expansion into the UK Air domain, owning sales, pipeline, bids, contracts and account growth. Build senior customer and partner relationships, translate AI/ML capability into operational outcomes, and ensure solutions are deliverable and strategically aligned while working with multidisciplinary teams in secure defence contexts.

Entry-level data science and engineering intern contributing across the data product lifecycle: ingesting and transforming data, building and maintaining pipelines, supporting model development and analysis, creating dashboards and presentations, and collaborating with cross-functional teams to turn data into actionable insights for media and marketing clients.

Lead and build a marketing data science and analytics function to unify marketing measurement (MMM, attribution, mobile measurement), experimentation, and MarTech. Hire and manage teams across analytics, data science and engineering, set measurement standards, partner with Finance and senior stakeholders, drive predictive analytics and media optimisation, govern privacy-first measurement across markets, and manage vendor and build-vs-buy decisions.

Design, build, and deploy AI and automation solutions to accelerate clinical trial data workflows. Develop scalable document processing, data extraction, and analytical tools, ensure regulatory and data-quality compliance, and provide technical leadership to drive adoption across scientific teams.

Undergraduate year‑in‑industry placement to scope, prototype and evaluate optical techniques for higher‑resolution, robust 3D optical interferometry in elastohydrodynamics. Work spans mechanical design, optics, data analysis and software engineering; own and deliver a one‑year R&D project within a multidisciplinary team.

Lead and build Alto's data science capability: define roadmap, develop and productionise predictive models (churn, propensity, forecasting), run experiments, create segmentation and scoring, surface insights via ThoughtSpot, collaborate with engineering and commercial teams, and hire/mentor a data science team.

Build and evolve a reusable data and ML platform: implement IaC and CI/CD, develop Python/Spark components, support data/ML lifecycle and AgentOps, improve observability, enforce security and governance, and collaborate across engineering and data teams.

Design, build, and maintain scalable data pipelines and platform components using Spark/PySpark on Azure. Develop reusable templates, enforce data engineering best practices (CI/CD, testing, observability), support product teams, and optimise pipeline performance, reliability, security, and cost-efficiency.

Lead full-cycle technical recruiting for Engineering and Data Science across EMEA. Partner with hiring managers to define needs, influence compensation and leveling, source and screen candidates, manage ATS tracking, drive internal mobility, and deliver data-driven recruiting programs to build diverse, high-performing teams.

Manage and grow relationships with Western Europe e-commerce clients as a trusted advisor. Ensure CDP delivers measurable value, align platform with client strategy, drive adoption, advise on analytics and marketing best practices, and balance client and Bloomreach objectives to create win-win outcomes.

Lead and grow a data science practice for energy and utilities clients: build and coach teams, design and scale AI/advanced analytics products, lead business development, manage high-value programmes, engage senior stakeholders, and contribute market-facing thought leadership.

Lead and manage data science teams in optimizing logistics through ML and operations research, ensuring research translates into production-scale solutions.

Lead and deliver end-to-end marketing analytics and MMM projects for global clients. Translate econometric and MMM insights into actionable business recommendations, manage client relationships, and lead teams (3–8 consultants). Support project planning, design, and implementation while communicating results to technical and non-technical stakeholders.

The Data Science Manager will collaborate with business partners, oversee predictive model building, manage a team, and deliver analytical insights to drive business decisions.

This role invites speculative applications for various tech positions. Candidates with skills in Salesforce, DevOps, AWS, and user experience are encouraged to apply.

Lead and own LoopMe's AI throttling system and related AI products end-to-end. Manage a team of four data scientists/ML engineers, define roadmap, partner with commercial and operations teams, deploy and monitor production models, measure causal business impact, and maintain technical quality across modelling and systems.

Lead the data science organization to deliver AI products, mentoring teams and executing a strategic vision for machine learning applications.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.