Top Data Jobs in London

Owns the full sales cycle for Data and AI solutions, from customer discovery and data-readiness assessments through proposals, negotiation, and close. Develops pipeline, sells modern data platforms, governance, analytics, cloud, and applied AI services, and builds relationships with strategic technology decision-makers and Microsoft partners. Translates technical capabilities into business outcomes, supports bids and tenders, forecasts accurately, and drives follow-on transformation and AI adoption.

Maintains Cloudflare’s global data center network infrastructure across remote colocation sites. Responsibilities include configuring network equipment, ensuring operational availability, managing contractors and vendors, creating SOPs and operational plans, supporting deployments and migrations, improving processes through automation and AI tools, troubleshooting infrastructure, and participating in a 24/7 on-call rotation. The role also involves basic program management, documentation, status reporting, and limited travel.

Develop, deploy, validate, and support machine learning models that detect A2A fraud, scams, and mule activity. Analyze large datasets, conduct customer proof-of-value exercises, improve production models, research new detection solutions, and collaborate with Product, Customer Delivery, and Data Science teams to deliver measurable customer outcomes.

Supports the firmwide privacy program by advising on privacy requirements, conducting risk and maturity assessments, developing controls, managing governance documentation, and supporting training and complex cross-functional initiatives. The role requires knowledge of global privacy laws, including GDPR and CCPA, experience with data protection impact assessments, and the ability to work independently with stakeholders across functions.

Develops reliable risk datasets, KRIs, dashboards, management reporting, and early-warning capabilities across enterprise and operational risk areas. Partners with risk stakeholders to define indicators, assess data quality, analyze trends and anomalies, calibrate thresholds, and translate requirements into practical data solutions. Uses SQL, Python, visualization tools, Snowflake, AI-enabled workflows, and automation to modernize risk reporting while maintaining validation, traceability, and human oversight.

Analyze complex datasets to identify actionable payment optimization insights for merchants and internal stakeholders. Build scalable data frameworks, self-service analytics tools, ETL pipelines, and data visualizations. Use Python, SQL, PySpark, statistics, LookML, and Looker to support automation, experimentation, and business decision-making. Serve as a payment optimization subject matter expert while managing stakeholder relationships and clearly communicating recommendations.

Own the requirement-to-reporting lifecycle for compliance analytics, translating business needs into functional specifications, metrics, data mappings, transformation logic, and reporting products. Partner with business leaders, data engineers, and executives to address data gaps, define KPIs, build scalable pipelines, conduct UAT, validate data integrity, and deliver intuitive dashboards using Tableau, Power BI, Mode, or similar tools.

Build customer-facing, data-first frontend experiences for schema exploration, data lineage, query building, semantic modeling, dashboards, and AI-assisted interfaces. Develop reusable Web Components and shared component systems, collaborate with UX and backend teams, improve architecture, testing, accessibility, and deployment practices, and mentor engineers. The role spans Ember, React, Lit, TypeScript, visualization libraries, modern build tooling, monorepos, and frontend CI/CD.

Own and improve Wise’s marketing data activation ecosystem, including Reverse ETL pipelines, SQL/dbt models, monitoring, observability, identity resolution, and advertising-platform integrations. Diagnose end-to-end data flow issues and collaborate with analytics, data, engineering, and paid media teams to deliver reliable customer audiences and conversion signals.

Leads data management and transformation initiatives across Markets Operations, focusing on reference data, data quality, KYC controls, governance, analytics, and trade lifecycle processes. Partners with business, technology, and control stakeholders to deliver roadmaps, dashboards, remediation solutions, operating models, and risk controls. Oversees program governance, requirements, data flows, milestones, documentation, dependencies, and issue escalation.

Lead Perk’s 40-plus-person data organization and define its company-wide data strategy, infrastructure roadmap, governance, privacy, and AI adoption. Build data into core product infrastructure, improve quality and scalability, shift the organization from reactive reporting to strategic insight, and develop senior leaders. Partner with Product, Engineering, Finance, Marketing, Revenue, Customer Care, and People leadership while owning the data budget, organizational design, and executive-level outcomes.

Leads commercial analytics and insights for pharmaceutical brands across the UK and Ireland. Responsibilities include market, customer, competitive, and performance analysis; forecasting; market research; dashboard and data capability enhancement; customer segmentation and campaign optimization; and advising senior commercial leaders. The role also coaches junior analytics colleagues and promotes data-driven decision-making.

Lead strategic and operational data science through quantitative analysis, forecasting, experimentation, and data storytelling. Mentor data scientists, advise cross-functional leaders, define metrics and forecasts, and build scalable decision-support systems. The role also contributes to AI and machine-learning systems that optimize product behavior, pricing, risk, allocation, and customer experiences, with an emphasis on rigorous validation, governance, and measurable outcomes.

Develop, test, and support reliable, high-performance distributed Java applications for real-time streaming and concurrent workloads. Partner with stakeholders, present and review designs, improve reliability/observability/performance, and support production releases to meet SLAs within BGM Data & Analytics.

Own the end-to-end lifecycle of proprietary private markets data across EMEA, including stakeholder outreach, data acquisition, validation, maintenance, quality improvement, and coverage growth. Build relationships with fund managers, investors, and clients; identify valuable data opportunities; apply analytical judgment and AI-enabled workflows; and contribute to strategic and revenue-generating initiatives while ensuring operational excellence and reliable execution.

Leads software engineering strategy and development for AI/ML data platforms. Designs reusable frameworks, architects governed agentic AI development workflows, builds secure and scalable cloud-native applications, and operates 24x7 tier-1 services. Influences technical, product, and business leaders; drives adoption of engineering methods, responsible AI controls, automation, and platform capabilities across teams.

Data Science Interns will complete a real-world data science project using machine learning techniques, develop customer-impacting solutions, prioritize product improvements, and experiment with advanced algorithms. The role includes mentorship, intern learning sessions, and collaboration within a global cohort. Candidates must be graduating in 2028, available for a 10-week summer internship, understand computer science and machine learning fundamentals, use Python and SQL, and be eligible to work in London without visa sponsorship.

Support data science projects that improve Wise products and customer experiences. Develop machine learning solutions, experiment with advanced algorithms, identify high-impact opportunities, and collaborate with autonomous teams across areas such as marketing, treasury, and fraud. The role includes learning Wise’s domain and technology stack, contributing ideas during planning cycles, and applying data science methods to real-world problems.

Designs and operates production-grade data pipelines and governed data products for technology resiliency and recovery-risk analytics. Responsibilities include data modeling, integration, lineage, quality controls, metadata management, distributed systems, database optimization, and scalable architecture. Partners with engineering, cybersecurity, controls, architects, analysts, and business stakeholders to translate requirements into technical solutions and deliver measurable operational outcomes.

Develop AML risk detection systems using supervised, unsupervised, semi-supervised, and generative AI techniques. Build and evaluate machine learning controls, optimize precision-recall trade-offs, create investigator insights, automate data labeling and retraining pipelines, deploy production-grade Python services, and collaborate cross-functionally with operational teams. The role also includes mentoring junior colleagues and solving financial crime problems at global scale.

A 12-month placement supporting Hilton’s Global Safety & Security team through data analysis, risk assessment, incident reporting, forecasting, and project management. The participant will analyze accident, claim, insurance, guest assistance, and vendor incident data to identify trends and inform mitigation strategies across occupational, food, fire, physical security, crisis management, and compliance areas. The role includes mentorship, cross-functional collaboration, and structured professional development at Hilton’s EMEA headquarters in Watford.

Develop and support credit risk and pricing models for lending products. Responsibilities include data exploration, feature engineering, statistical analysis, model monitoring, deployment support, documentation, and collaboration with Credit Strategy, Product, Engineering, and Data Engineering teams. The role is designed for an early-career data scientist with strong quantitative skills and an interest in credit and financial services.

Coordinate AI and data governance requests across HR and Employee Experience. Manage intake, triage, routing, documentation, approvals, SLA tracking, stakeholder follow-up, remediation, and escalation for governance cases. Partner with HR, privacy, legal, compliance, risk, control, and technology teams to progress complex or high-risk use cases through approval. Improve ticket quality, workflows, templates, and guidance while maintaining accurate, auditable records.

Build and productionize classical machine-learning models for lead quality and traffic performance, including classification, ranking, anomaly detection, and forecasting. Apply decision science through contextual bandits, experimentation, causal methods, and off-policy evaluation to improve agent decisions. Monitor models, measure commercial impact, establish guardrails, and collaborate with AI engineers, product managers, platform teams, and business operators.

Lead the strategy, roadmap, delivery, governance, adoption, and execution of BlackRock’s enterprise Data Marketplace and data product ecosystem. Translate business and governance needs into product capabilities, prioritize engineering backlogs, and coordinate Product, Engineering, Operations, Risk, Compliance, and business stakeholders. Drive onboarding, documentation, release readiness, data reuse, AI-ready capabilities, and scalable data governance across investment and operational functions.