Top Data Jobs in London

As a Lead Data Engineer, you will design and develop software for data processing, lead a team, ensure quality, and manage technical proposals.

Lead cross-functional initiatives to enhance KOL data products, translating customer needs into development initiatives and ensuring data quality and usability.

The Principal Architect will lead the design and strategy of next-generation data center architecture, focusing on software-defined infrastructure, workload management, and governance, with extensive experience required in various technologies.

The Senior Data Engineer will design and implement data pipelines for fraud prevention, collaborate with teams, and ensure high quality code while participating in agile methodologies.

As the Director of Data Science, you'll mentor teams, oversee projects, drive data-driven decisions, and implement AI and ML solutions while enhancing our data pipeline.

Use econometrics, causal inference, experiments and ML to answer business questions affecting restaurants, riders and customers. Produce analytical insights, run experiments, collaborate with stakeholders, and impact growth and profitability using R/Python and SQL.

Partner with FP&A and senior stakeholders to deliver commercial and strategic analysis, own trading insights and executive KPIs, build and automate dashboards, develop end-to-end data models and pipelines (dbt), and enable AI-driven self-serve analytics for business decisions.

Conduct hands-on analysis of operational data across acquired businesses to find inefficiencies and opportunities, validate and profile inbound data, support internal data-product requirements, contribute to ETL and data preparation, and communicate insights to operators and leadership.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

As an Engineering Manager, oversee data engineering and analytics projects, while leading teams focused on data platforms and governance. Foster collaboration and ensure operational compliance.

Senior, client-facing role leading Data & Analytics value-creation work across the UK and Europe. Advise PE sponsors, CFOs and portfolio teams to translate business problems into KPI-driven analytics, operating models and commercial insight. Lead delivery teams, ensure quality, support business development, and travel extensively across Europe to run workshops, readouts and engagements.

This role involves leading data analysis, managing datasets, developing predictive modeling solutions, and providing analytic thought leadership for business problems.

Senior technical authority for electrical engineering across EMEA data centre portfolio. Lead design governance, resilience validation, technical assurance, and delivery of HV/MV/LV, UPS, generator, protection, and energy systems from concept through commissioning. Drive reference designs, standards, consultant oversight, innovation (battery storage, liquid cooling), and cross-functional alignment to ensure constructability, operational readiness, and long-term platform performance.

Mid-level Data Scientist (2–5 years) focused on risk, fraud, and compliance. Build and deploy ML models and deterministic rules, run funnel and A/B experiment analyses, create dashboards, partner with Product/Growth/Engineering, and improve data quality and instrumentation.

The Senior Applied Data Scientist will implement, support, and develop complex models, leveraging machine learning to provide actionable insights for retail clients.

The Associate Data Scientist will work on developing and optimizing machine learning models, collaborating with teams to tackle pricing and matching challenges.

Lead the development and integration of AI solutions, focusing on advanced modeling, generative AI architecture, and building user interfaces for decision-making tools.

Lead and grow the data engineering and ML teams, own technical strategy and delivery for data infrastructure and model estate, translate business goals into scalable data and ML solutions, partner with product/marketing/commercial leadership, hire and develop engineers, and drive adoption of AI-led development while remaining hands-on.

As a Graduate Data Scientist, you'll work on fraud detection, anti-money laundering, and claims automation, implementing data engineering and developing machine learning models.

The role involves managing and optimizing data annotation workflows, ensuring data quality, and acting as an advisor to clients while collaborating with technical teams.

The Graduate Data Scientist will support data advisory engagements by documenting data processes, constructing architecture diagrams, and communicating strategies to stakeholders. They will utilize databases, SQL, and cloud platforms.

The Data & MI Analyst will support regulatory reporting transformation by ensuring data quality, performing reconciliations, and building MI dashboards while collaborating with stakeholders.

Lead design and evolution of scalable real-time and batch ETL pipelines and data platform. Own performance, reliability, and data quality; drive architecture and tooling choices; collaborate with product and backend teams; mentor engineers and shape target architecture to support trader-facing analytics and low-latency data needs.

Collect, clean, and transform large datasets; build and maintain data models and reports (using Snowflake and BI tools); perform statistical and machine-learning analyses; define KPIs; ensure data governance and accuracy; present insights to stakeholders; collaborate with data engineers and follow software development best practices.

Build and lead a global reliability and technical assurance function for Vantage's data center fleet. Define fleetwide reliability baselines and risk models, perform technical inspections across electrical, mechanical, controls and commissioning, drive corrective actions and closed-loop learning, establish standards, executive reporting, and scale a central assurance team.