Top Data Jobs in London

Analyze Cloud Marketplace operational, commercial, transactional, pricing, and billing data to identify anomalies, workflow issues, revenue leakage, and process inefficiencies. Investigate root causes, coordinate remediation, validate quote-to-invoice integrity, build dashboards and reports, and present actionable insights. The role also owns data analysis approaches, anomaly detection, data quality improvements, and platform performance reporting while partnering with product, development, commercial, and finance teams.

Leads Gartner thought leadership and client advisory research on data management and AI readiness. Develops market insights, analyzes client challenges, predicts trends, creates research and presentation content, supports sales and conferences, and advises executives. The role also establishes analyst-team viewpoints, reviews content, improves research processes, mentors colleagues, and represents Gartner’s methodology. Requires deep expertise in data architecture, data operations, database and integration practices, and AI-ready data management, with up to 25% travel.

Own marketing analytics, funnel reporting, dashboards, attribution, cohort analysis, and conversion rate optimization. Analyze customer journeys from acquisition through retention, identify funnel losses, and design and evaluate A/B and multivariate experiments across landing pages, signup, onboarding, and email. Partner with marketing, product, engineering, RevOps, sales, and leadership to improve measurement, define trusted metrics, and translate findings into prioritized growth recommendations.

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 customer-facing Data and AI technical engagements from discovery through proof-of-value and delivery handover. Lead workshops, architecture design, demonstrations, proofs of concept, proposals, and technical evaluations. Partner with Revenue, Engineering, Product, Marketing, and cloud or SI partners to support account strategy, co-selling, and go-to-market activities. Advise enterprise customers on modern data platforms, AI solutions, governance, ROI, and technical implementation while creating reusable reference architectures and demo assets.

Build, evaluate, deploy, and monitor statistical and machine learning models for credit risk, fraud prevention, customer engagement, and operational efficiency. The role involves data exploration, feature engineering, experimentation, production monitoring, SQL and dbt data workflows, Python development, documentation, and collaboration with Product, Risk, Compliance, Operations, and Engineering teams.

Build and maintain batch and real-time data pipelines, data models, dashboards, and data products supporting front-office trading. Responsibilities include orchestration, schema and ORM design, SQL optimization, data quality controls, streaming architectures, Python visualization, DevOps, monitoring, testing, security, and stakeholder collaboration. The role owns delivery end to end and contributes to architecture and engineering standards.

Use data analysis, experimentation, statistical modeling, and forecasting to guide Spotify’s product and business strategies. Analyze A/B and quasi-experiments, identify growth opportunities, assess new initiatives, and translate complex findings into actionable recommendations for senior leadership. Partner with cross-functional business teams and communicate insights across varying technical audiences.

Monitor football betting markets, analyze live and historical data, adjust odds based on real-time events, and identify trading opportunities. Collaborate with analysts to improve predictive models while maintaining accuracy under pressure during live matches. The role requires strong mathematical ability, comprehensive football knowledge, analytical decision-making, and flexibility for weekend and evening shifts.

Design, build, and operate scalable batch and near-real-time data pipelines, ETL/ELT workflows, integrations, data models, and curated data products. Own solutions through deployment, monitoring, troubleshooting, and continuous improvement while implementing testing, governance, security, observability, and CI/CD practices. Provide technical leadership, mentor engineers, collaborate with cross-functional teams, and enable trusted, AI-ready player data for analytics and business transformation.

Manage month-end reporting, management accounts, balance sheet reconciliations, departmental cost allocation, journals, budgeting, forecasting, statutory accounts, audits, tax compliance, and process improvements. The role requires a part-qualified accountant with three years of finance or audit experience, advanced Excel skills, and the ability to manage competing priorities in a fast-paced startup environment.

Lead Doccla’s data function during a 14-month maternity cover, managing analysts and engineers, shaping NHS value-based contracts, designing healthcare intervention evaluations, and owning population health analytics, data partnerships, quality, architecture, and technical standards. The role requires strong healthcare data expertise, quasi-experimental evaluation, health economics, SQL, analytics engineering, and senior-level communication with NHS leaders, clinicians, and commissioners.

Lead strategy and backlog for a data and insights platform, drive integrations and analytics features, translate market insights into product requirements, lead initiatives end-to-end, analyze outcomes, champion experimentation, and align stakeholders to deliver data-driven product innovation that improves player experience and commercial outcomes.

Senior Data Scientist responsible for developing and deploying machine learning solutions, conducting advanced statistical analysis, defining business metrics, and solving complex planning and forecasting problems. The role involves querying and analyzing data with SQL and Python, creating visualizations and stakeholder reports, influencing business decisions, implementing algorithms, managing project delivery, and mentoring other data scientists.

The Data Engineer will build data pipelines for materials science, ensuring data quality and collaborating with ML researchers while managing large datasets.

Leads claims data analytics for UK Claims Operations, developing KPI monitoring, regulatory and operational reporting, self-service dashboards, statistical analyses, and data-driven insights. Supports claims strategy, process improvement, stakeholder collaboration, data literacy, and management decision-making. Ensures reporting accuracy, compliance, timely delivery, and knowledge sharing across the claims team.

Lead cost management and quantity surveying for large-scale data centre projects across the UK and Europe. Responsibilities include cost planning, procurement strategy, tender management, contract administration, change and risk management, forecasting, financial governance, dispute support, stakeholder management, client development, team leadership, and project delivery through all RIBA stages. The role requires data centre or advanced technology sector experience, strong commercial judgment, and regular travel to Milan.

Develop and operate full-stack web applications across the complete software lifecycle, including ideation, design, prototyping, development, deployment, maintenance, and support. Build scalable frontend and backend solutions using React, JavaScript, TypeScript, Python, microservices, event-based architecture, and GCP. Collaborate directly with stakeholders, independently deliver projects, and contribute to deployment and continuous development practices.

Leads reward data and analytics for global Pay Transparency Directive compliance. Responsibilities include pay-gap analysis, statistical assessment, data validation, statutory reporting, remediation modelling, Syndio administration, governance, audit documentation, and operational transition. Partners with Reward, Payroll, HR Technology, Legal, Privacy, Finance, and country stakeholders to ensure accurate, repeatable, compliant, and explainable reporting across multinational operations.

Leads and develops a Security Operations team, serves as the technical escalation point for cyber incidents, improves security controls and resilience, and drives security roadmap initiatives. The role partners with engineering, product, architecture, and senior leadership while promoting secure-by-design practices, operational excellence, KPI management, and continuous team development.

Build and maintain batch and streaming data pipelines for the QiCore warehouse. Migrate acquired-business data, model datasets for analytics and reporting, monitor pipeline health and data quality, and support repeatable platform migrations. The role requires production SQL and Python, cloud warehouse or big data platform experience, governance and testing knowledge, orchestration, version control, and collaborative engineering practices.

Leads and develops the data engineering team, owns technical strategy and infrastructure delivery, and ensures data platforms scale with business growth. Partners with product, marketing, commercial, and executive stakeholders to prioritize impactful data initiatives. Establishes engineering standards, supports AI-led development, remains technically hands-on, and translates complex technical topics into commercially relevant outcomes.

Own the architecture and design standards for QiCore, the company’s data warehouse. Lead customer identity, PII, consent, governance, retention, access control, data quality, and modelling practices. Migrate acquired businesses into a unified data model, prototype and debug pipelines using SQL and Python, guide engineers, and translate business needs into a scalable platform supporting future AI initiatives.

Build credit risk, pricing, credit limit, and customer lifetime value models for a business credit card. Lead analytical projects from problem framing through business decisions, using Bayesian methods to quantify uncertainty with limited data. Collaborate with commercial, product, engineering, operations, credit risk, and data science teams. Apply customer and business understanding to optimize card pricing, spending, retention, cross-sell, and combined credit exposure.

Lead complex data science and machine learning projects from technical scoping through production delivery. Set technical direction, architect reliable solutions, define roadmaps, manage technical risk, and oversee multidisciplinary workstreams. Lead client engagements, support commercial opportunities, establish technical best practices, and mentor data scientists and managers. The role also requires influencing engineering, infrastructure, commercial, and business-unit initiatives while delivering practical outcomes under commercial pressure.