Top Data Jobs in London

Builds and configures Medidata Rave EDC databases for clinical trials, including eCRF packages, form dynamics, edit checks, custom functions, coding, migrations, integrations, and technical specifications. Collaborates with clinical data management and scientific teams, provides subject-matter expertise for complex builds, trains junior staff, and contributes to process and system improvements. Requires at least five years of EDC database-building experience, advanced custom-function programming, clinical trial experience, and knowledge of GCP/ICH and CDASH.

Leads sample, kit, laboratory, biomarker, and associated data operations across global clinical studies. Oversees planning, logistics, vendor activities, data quality, dashboards, database queries, transfers, and database lock support. Collaborates with clinical, data management, biostatistics, laboratory, and operational teams to ensure protocol compliance, regulatory alignment, and high-quality precision medicine execution.

Lead Data and AI pre-sales activities, translating client needs into commercially viable solutions. Support opportunity qualification, workshops, bids, proposals, solution design, and account strategy while collaborating with sales teams and technology partners. Present solutions to technical and executive audiences, develop propositions and thought leadership, monitor market trends, and share customer insights. Travel to client sites and industry events as required.

Own end-to-end data science initiatives within an embedded product team. Analyze customer behavior, identify opportunities, design and evaluate experiments, define metrics, build forecasting, personalization, and prediction models, and deliver actionable recommendations that influence product and monetization strategy. Collaborate with technical and non-technical stakeholders to drive measurable customer and business impact.

Designs and maintains data pipelines, models, visualizations, and data infrastructure across Google Cloud and Microsoft Azure. Integrates marketing and sales data, performs exploratory analysis using SQL and Python or R, delivers commercial performance reporting, ensures data quality, and analyzes customer journeys across ecommerce and marketing websites to recommend improvements.

Develop predictive models, machine-learning, AI, and Generative AI solutions for Crop Protection R&D. Analyze complex scientific datasets, identify valuable AI use cases, validate and govern models, and deploy scalable analytical applications. Partner with scientists, software teams, and stakeholders to support product discovery and decision-making. Communicate insights, track performance metrics, document methodologies, and mentor junior data scientists.

Designs end-to-end data architectures and platforms for complex client programs, covering ingestion, orchestration, governance, security, cost optimization, and observability. Leads engineering teams, translates business needs into scalable solutions, advises clients on data and AI transformations, and provides strategic technical leadership. Responsibilities also include assignment delivery, team development, thought leadership, bid leadership, and business growth in a consulting environment.

Owns data collection, analysis, reporting, and dashboard development across Sales, Product, Marketing, and executive teams. The role identifies trends, risks, and opportunities; translates complex findings into strategic recommendations; ensures data quality; supports AI and automation initiatives; and promotes data literacy. The analyst partners cross-functionally to improve business processes and inform growth decisions across a global digital art marketplace.

Lead Ocado Group’s business intelligence and agentic analytics strategy, overseeing Looker and Celonis platforms, semantic-layer migration, AI evaluation, telemetry, governance, and partner-facing OSP Insights. Own product vision, roadmap, commercial value articulation, partner onboarding, and operational support while building and mentoring a high-performing analytics team.

Design and analyze experiments, build statistical and machine-learning models, and use data to improve third-party acquisition through brokers and partners in Germany. The role covers funnel conversion, pre-qualification, customer take-up, lifetime value, competitive positioning, and lending offer terms. Responsibilities include framing ambiguous commercial questions, conducting causal analysis, translating findings into recommendations, collaborating with product and commercial teams, and communicating technical results clearly.

Develop machine learning models and decision-support tools for pricing optimization, margin forecasting, deal scoring, customer segmentation, and opportunity analysis. Analyze commercial datasets, create dashboards, support A/B testing, and translate insights into tools for sales, finance, and pricing teams. Collaborate with business intelligence, data engineering, pricing, and deal operations stakeholders to improve commercial decision-making.

Principal individual contributor responsible for shaping how Mintel data, content, and AI capabilities are delivered through client-controlled integrations. Conducts client discovery, evaluates workflows, defines integration-facing contracts, improves data structure and descriptions, tests assistant and system performance, and translates client evidence into product roadmaps. Partners with Data Product, Engineering, Architecture, Product, Sales, and Account Management while developing use cases, standards, enablement materials, and thought leadership.

Build production data pipelines that transform third-party datasets into research-ready data and live signals. Partner with quantitative researchers to engineer features, develop signals, validate and normalize data, and use LLM-based agents to automate ingestion-to-signal workflows. The role also involves creating reusable tools that help researchers and data scientists scale their work.

Leads EMEA employee relations delivery across seven jurisdictions, overseeing case intake, triage, investigations, performance, absence, conduct, consultations, litigation support, reporting, and closure. Coaches managers and leaders on sensitive employment matters, coordinates with Legal and counsel, maintains country playbooks and case controls, and uses ER data to improve processes and training. Requires strong knowledge of EMEA employment practices, multilingual capability, HRIS tools, and the ability to manage complex, confidential cases across countries.

Own the roadmap for a core data engine, prioritizing datasets, defining data structures and access, and ensuring product value reaches customers. Partner with engineers, analysts, commercial teams, and sales; prototype with messy datasets; manage data quality, metrics, user research, release planning, and stakeholder decisions. The role requires SQL fluency, familiarity with LLM or agent-based pipelines, and experience delivering technical or data-heavy products from user problem through launch.

Owns complex finance reporting datasets, dashboards, reconciliations, controls, and cross-system investigations across entities, currencies, and accounting bases. Automates reporting with SQL, Power Query, Power BI, VBA, and Excel; establishes data quality and source-to-report controls; translates business requirements into data rules and mappings; supports finance transformation, governance, testing, documentation, and business-as-usual adoption across Finance, Data, IT, and related functions.

Own the product roadmap and portfolio prioritization for vehicle data and telematics products supporting regional revenue growth. Lead customer discovery, product strategy, solution validation, reporting frameworks, feedback loops, and cross-functional execution from discovery through launch. Partner with UX, engineering, data science, project management, customers, and senior leadership while mentoring product managers and driving data-informed decisions using product KPIs and user engagement metrics.

Develop and support enterprise data platforms using Python, SQL Server, Oracle, ETL, and business intelligence technologies. Build greenfield data-centric solutions, create dimensional data models, optimize queries, support dashboards, and collaborate with Operations, Risk, Finance, and investment-engineering teams. The role also requires translating complex business requirements, participating in Agile delivery and code reviews, supporting CI/CD, and embracing AI-enabled development.

Leads delivery of a North American data centre project portfolio, providing executive oversight, governance, risk management, performance assurance, client engagement, and corrective action. The role develops delivery leaders, coordinates resources and capabilities across dispersed teams, improves consistency and quality, and sponsors programmatic delivery improvements for large-scale technology infrastructure projects.

Leads the global market data audit and compliance program, overseeing risk-based planning, complex client and vendor reviews, evidence-based findings, remediation, licensing, revenue recovery, and settlement negotiations. Manages auditors, stakeholder escalations, governance, reporting, and controls involving restricted information. Drives process improvement, automation, dashboards, and responsible AI adoption while ensuring market data licensing obligations and audit decisions are accurate, defensible, and consistently documented.

Lead the design and delivery of scalable, metadata-driven data engineering solutions using Databricks and Azure services. Develop ingestion frameworks, orchestration processes, ETL pipelines, and CI/CD practices while improving performance, reliability, governance, and security. Collaborate with stakeholders, data scientists, and analysts to translate business needs into effective solutions. Lead technical design discussions, make architectural decisions, manage multiple deliverables, and mentor junior engineers.

Develop propensity, segmentation, statistical, and machine-learning models to support business decisions. Operationalize analytical data products, lead end-to-end analytics and AI projects, identify actionable insights, and communicate recommendations to senior stakeholders. The role focuses on solving real business challenges, measuring outcomes, and helping Dogs Trust improve its impact through data-driven decision-making.

Leads complex data engineering initiatives, designing metadata-driven ingestion frameworks, orchestration processes, scalable Databricks and Azure data solutions, and robust ETL pipelines. Establishes CI/CD, DevOps, governance, security, and data engineering best practices; optimizes pipeline performance and reliability; collaborates with stakeholders, analysts, and data scientists; leads technical architecture decisions; and mentors junior engineers.

Leads the data quality engineering team and owns correctness across client-facing APIs, streaming systems, cloud data delivery, reference data, and security master data. Builds adaptive quality checks, AI-assisted testing, governance and lineage tooling, resilience and load tests, and defect detection processes. Maintains OpenMetadata or equivalent governance systems and expands quality coverage across trading and analytics products.

Leads complex global consulting engagements for life sciences quality organizations, including project delivery, $1M+ business development, team leadership, thought leadership, and C-suite advisory. Focuses on improving quality operating models, organizational change, and business value across pharmaceutical, medical technology, and consumer product companies using technology, data, and AI.