Top Data Jobs in London

Leads hands-on data science and advanced analytics for drug development using clinical trial, real-world, omics, imaging, and biomarker data. Develops predictive models, machine learning and statistical analyses, reproducible pipelines, data quality frameworks, and scalable cloud-based workflows. Collaborates with statisticians, clinicians, translational scientists, engineers, and data teams to support clinical decisions, biomarker discovery, precision medicine, and innovative trial strategies. Provides technical mentorship, communicates findings, and coordinates multiple concurrent projects.

Lead the design, development, optimization, and operation of scalable data pipelines, ETL/ELT processes, data platforms, and analytical data models. Translate data architecture into production solutions, ensure data quality and performance, optimize infrastructure costs, and support regulatory reporting. Provide hands-on coding, infrastructure, troubleshooting, code reviews, and technical leadership while mentoring junior and mid-level engineers and collaborating with architects, product managers, data scientists, and business stakeholders.

Leads digital data and analytics roadmap delivery, data governance, taxonomy, measurement frameworks, dashboards, experimentation, and AI-enabled analytics. Partners with marketing, technology, and client experience stakeholders to translate business needs into trusted reporting, reusable data products, actionable insights, and Adobe Experience Platform requirements.

Leads a RevOps Data Analyst team and revenue analytics capability. Responsibilities include managing analytical priorities, producing commercial insights, supporting forecasting and planning, owning dashboards and reporting, governing metrics and data quality, and partnering with Finance, Sales, Customer Success, Marketing, Product, and RevOps stakeholders. The role also supports CRM, BI, and data-platform transformation across legacy businesses while translating complex analysis into actionable recommendations for senior commercial leaders.

Develop and deliver personalized CRM campaigns across email, push notifications, in-app messaging, on-site experiences, and performance marketing channels. Use Braze, Movable Ink, customer data, and analytics to optimize engagement and campaign performance. Collaborate with cross-functional agile teams while ensuring FCA, GDPR, and internal governance compliance.

Designs, builds, and maintains dimensional data models and quality-assured analytical datasets using dbt. Integrates complex data sources, manages metadata, performs data profiling, and supports data quality and governance standards. The role involves gathering requirements, collaborating with data engineers and analysts, documenting models, and enabling tools such as Airflow. It requires strong stakeholder communication and experience delivering analytics engineering solutions in complex or public-sector environments.

Supports data science and AI consulting projects by cleaning and exploring datasets, developing and evaluating statistical and machine learning models, prototyping language-model solutions, preparing visualizations and findings, and communicating results to technical and nontechnical audiences. The role emphasizes reproducible Python code, documentation, collaboration, and learning through client-focused projects.

Develop data science and AI solutions for government and public-sector clients. Responsibilities include defining analytical problems with subject matter experts, preparing data, building and evaluating statistical, forecasting, machine learning, and language-model prototypes, presenting findings, creating reproducible code, contributing to proposals, and collaborating across technical teams.

Leads enterprise data strategy, analytics, business intelligence, data science, experimentation, and game economy optimization. Builds trusted data platforms, governance, metrics, and decision frameworks while driving predictive analytics and responsible AI. Oversees monetization, segmentation, pricing, and portfolio-wide game economy standards to improve player engagement, retention, lifetime value, and commercial performance. Manages distributed technical and commercial teams and partners with Product and Live Operations leadership.

Develops and executes sourcing and category-management strategies for data center-related direct and indirect spend. Leads spend analysis, supplier selection, RFPs, contract negotiations, cost optimization, implementation, supplier compliance, and long-range sourcing plans. Partners with internal stakeholders and senior management to deliver savings, governance, and value across construction, engineering, electrical, mechanical, facilities, and infrastructure categories.

Build and own pricing data science capabilities, including demand and elasticity models, forecasting, willingness-to-pay models, pricing optimization, experimentation, and causal analysis. Deploy and monitor machine learning systems, establish governed pricing metrics, and partner with Commercial, Finance, and Product to improve margin and revenue. Set analytical standards for pricing decisions and build reusable analytical capabilities.

Designs and operates data-protection controls across systems, products, endpoints, email, and cloud stores. Responsibilities include data discovery and classification, loss prevention, encryption, masking, secure disposal, privacy automation, threat modeling, incident investigation, digital evidence handling, and security metrics. The role serves as a technical authority, leading cross-functional privacy and security reviews and translating risks into reusable engineering controls, standards, guardrails, and policy automation.

Own the product strategy and roadmap for customer growth, using customer insight, market understanding, experimentation, and performance data to improve digital journeys. Build commercial cases, prioritize opportunities, lead initiatives from discovery through optimization, and collaborate with Product, Engineering, Design, Data, Commercial, and Marketing teams. Influence senior stakeholders, drive measurable outcomes, and coach others on product management best practices.

Develop statistical and machine learning sports models, engineer data assets, implement pricing engines in Python, and integrate solutions into Sportsbook applications. Build automated tests, validate data flows, support model deployment and lifecycle management, collaborate with Trading, Product, Engineering, and QA, and mentor junior data scientists.

Lead the technical direction of data engineering across client engagements. Design migration frameworks, streaming architectures, Lakehouse platforms, data integrity systems, and regulatory reporting pipelines. Provide architectural authority, review technical designs, select cloud services, mentor senior engineers, develop reusable delivery patterns, support hiring, and represent the consultancy externally. Shape proposals, scope technical engagements, present to senior stakeholders, and identify opportunities with existing clients.

Lead the technical direction of client data engagements, designing Microsoft Fabric and Azure data platforms, pipelines, models, testing, CI/CD, and operational practices. Manage and technically guide data engineers while remaining hands-on with complex challenges, incident response, and troubleshooting. Translate client requirements into technical roadmaps, collaborate with stakeholders, and ensure high-quality, commercially sound delivery using Python, PySpark, SQL, and modern data architecture patterns.

Designs, builds, and maintains production data pipelines using Microsoft Fabric, Python, and PySpark. Owns architecture, data modeling, CI/CD, reliability, troubleshooting, and technical decision-making. Collaborates with architects, product teams, and clients to translate requirements into robust solutions while mentoring junior engineers and improving engineering practices.

Supports Salesforce data governance, quality monitoring, compliance reporting, dashboards, automation, and data visualization. Maintains data dictionaries, Salesforce reports, Snowflake datasets, and Power BI dashboards while assisting with user training, system rollouts, data migrations, staffing administration, and operational projects. Partners with banking, operations, and technology teams to improve data accuracy, simplify processes, and support global reporting and automation initiatives.

Develop advanced automation and visual data processing workflows using AI tools, focusing on computer vision and data streaming techniques while ensuring system reliability and scalability.

Manages cost planning and commercial controls for data centre projects, including feasibility studies, estimates, procurement, tender analysis, valuations, variations, cost reporting, value engineering, and final accounts. Leads cost management teams, collaborates with clients and project stakeholders, supports bids and business development, monitors financial performance, and improves cost management processes and service quality.

Lead cost management and delivery of large, complex data centre projects across the UK and EMEA. Responsibilities include managing project and programme outcomes, coordinating procurement and contract strategies, applying European design and code requirements, developing industry relationships, and supporting business growth. Associate Directors additionally develop and deliver growth plans exceeding 20% annually while aligning sector ambitions with country-level business operations.

Oversee the design and operation of a multi-country federated registry platform using OMOP CDM. Manage vendor deliverables, data collection, ETL, mapping, quality checks, analysis plans, cohort definitions, and federated query specifications. Assess research feasibility, review analytical outputs, support publications, resolve data issues with vendors and registry sites, and collaborate with scientific committees and internal stakeholders to generate real-world evidence.

Lead Data Analyst responsible for advanced analytics, quantitative analysis, experimentation, and commercial modeling. Partner with Data Engineering to implement scalable pipelines, drive insights into decision-making, and embed customer research into operations. Mentor analysts, build data literacy, and influence cross-functional strategic and tactical decisions.

Lead the design and delivery of scalable data engineering solutions, pipelines, data models, and reporting infrastructure for WPP Media clients. Serve as a senior technical liaison, oversee data quality and governance, integrate new data sources, guide dashboard deployment, and mentor team members in data engineering, Power BI, and client engagement.

The role involves shaping data and AI strategies for financial institutions, guiding clients in harnessing AI for competitive advantage, and leading workshops to align stakeholders.