Top Data Jobs in London

Lead product strategy and delivery for Aladdin's wealth management technology. Define roadmap, embed AI and API-led integrations, drive cross-functional squads, engage clients and partners, and deliver scalable solutions for discretionary portfolios, advisory services, execution-only accounts, model management, trading, and reporting.

Leads Expedia B2B’s analytics organization, managing analytics managers and senior analysts while shaping multi-year analytics roadmaps and business strategy. Partners with senior stakeholders to drive measurable outcomes, guides statistical and machine learning applications, establishes analytics engineering and visualization practices, develops talent, and collaborates with data engineering, product, and machine learning teams on scalable solutions.

Design, build, and operate Akeneo’s Supplier Data Manager at enterprise scale. Develop reliable data-processing pipelines for messy supplier catalogues, including deterministic and LLM-powered extraction and classification. Create collaboration and governance workflows, ensure production observability and operational excellence, participate in customer discovery, and collaborate across teams. The role requires strong software engineering fundamentals, architectural thinking, debugging ability, end-to-end ownership, and clear communication.

Build and ship end-to-end features for Akeneo Supplier Data Manager across data-processing pipelines, backend services, and TypeScript/React frontend systems. Help process large, messy supplier catalogues using deterministic workflows and LLM-based extraction and classification. Own features through production monitoring and support, participate in customer discovery, collaborate across the Product Cloud, and develop engineering skills through pairing, code review, and mentorship.

Lead data science initiatives for KYC and customer onboarding, developing and managing machine learning models for document verification. Responsibilities include creating large image and tabular datasets, iterating deep learning models, optimizing performance, maintaining Python code, researching fraud prevention methods, collaborating with stakeholders, and mentoring junior data scientists.

Lead data architecture and engineering for Wise’s marketing platform, building resilient high-volume streaming and batch pipelines with Python, dbt, Airflow, Kafka, Trino, and Iceberg. Develop unified customer data platform datasets, own MarTech integrations, establish data quality and reliability standards, scope ambiguous technical problems, and mentor software engineers. Partner closely with marketing, product, analytics, and engineering stakeholders to deliver scalable acquisition infrastructure.

Lead development and deployment of machine learning and Generative AI systems for AML operations. Responsibilities include building EDD LLMs, evaluation datasets and automated testing frameworks, prompt optimization, shadow testing, production monitoring, human-in-the-loop workflows, and financial crime prevention solutions. The role also provides technical leadership, mentorship, architectural guidance, and cross-functional collaboration.

Lead development of production AI agents and machine learning workflows for B2B agentic commerce and payments. Responsibilities include agent orchestration, negotiation, onboarding, model training and serving on Kubernetes, evaluation, observability, secure software development, model-risk documentation, and technical leadership. The role also guides AI-assisted engineering practices and evaluates architectures with vendors and internal teams.

Designs and develops secure, scalable agentic commerce solutions for payments. Responsibilities include building agent orchestration components and MCP servers, developing Python services, creating Databricks data pipelines, supporting MLOps workflows, evaluating agent behavior, implementing observability, and improving operational stability. The role requires cloud-native engineering, API and event-driven services, LLM application development, responsible AI practices, Kubernetes, and secure production software delivery.

Lead architecture and engineering for B2B agentic commerce and machine-learning systems in global payments. Define multi-agent architectures, authorization, information barriers, MLOps pipelines, evaluation frameworks, safety guardrails, and model-risk evidence. Develop and review secure production code, establish AI-assisted engineering standards, integrate external agents, improve operational resilience, and guide technical teams and vendors. The role requires advanced Python, production LLM agent experience, secure distributed-systems expertise, and financial-services technology knowledge.

Leads commercial analytics and insights for pharmaceutical brands across the UK and Ireland. Responsibilities include market, customer, competitive, and performance analysis; forecasting market, patient, and revenue outcomes; designing market research projects; supporting dashboards and data platforms; and advising senior commercial leaders. The role also drives customer segmentation, campaign optimization, next-best-action initiatives, analytics innovation, and coaching of junior colleagues.

Analyze market, customer, brand, and competitor data to generate commercial insights, track KPIs, support forecasting and market research, maintain dashboards, and inform strategy. Partner with commercial and DD&T stakeholders on segmentation, targeting, campaign optimization, and data-driven decision-making while contributing to cross-functional projects.

Design and maintain scalable data platform infrastructure, ingestion pipelines, ETL/ELT workflows, data models, governance, reliability, and observability. Collaborate with analytics and engineering teams, support data warehouse architecture, participate in on-call incident response, document operational processes, and establish strong engineering practices for analytics and future AI capabilities.

Lead data science for Wise’s AML Risk team by developing machine-learning and GenAI detection systems, optimizing precision-recall tradeoffs, building coverage frameworks, and deploying production Python services. Hire and mentor specialists, collaborate with product, engineering, and operations teams, design model evaluation experiments, improve operational processes, and create investigator insights for detecting financial crime across global transactions.

Lead Preqin’s EMEA private markets data team, overseeing data acquisition, quality, coverage expansion, market engagement, and strategic execution. The role requires senior people leadership, commercial judgment, stakeholder relationship management, and deep private markets expertise. The leader will also drive data modernization and AI-enabled transformation, improve operational efficiency and scalability, and collaborate with Product, Technology, Commercial, and Data teams to deliver high-quality market intelligence to clients.

Manage strategic cybersecurity and data protection vendor partnerships to drive revenue, profitability, and market awareness. Develop partner-led go-to-market strategies, business plans, and commercial programs; identify growth opportunities; enable sales and presales teams; maintain executive-level relationships; manage accreditations; and track revenue, profitability, and strategic KPIs across partner portfolios.

Leads development of secure, scalable data platforms supporting batch, streaming, ML, and LLM workloads. Designs distributed data systems using Spark, Ray, Kafka, Iceberg, and OpenSearch; productionizes model training, deployment, monitoring, and lifecycle management; and builds governed LLM solutions. Provides technical leadership, code review, incident response, vendor evaluation, responsible AI guidance, automation, and mentorship across engineering teams.

Build, analyze, maintain, and optimize scalable data pipelines and complex data infrastructure. Develop ETL processes, data models, algorithms, and production software while working with large datasets and distributed batch processing. Collaborate with global engineering and product teams through analysis, prototyping, development, deployment, and maintenance. Apply data engineering, database, cloud, workflow orchestration, and software engineering practices in a dynamic agile environment.

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.

Owns HPE Alletra Storage MP X10000 sales across the UK, Saudi Arabia, and UAE. Develops the regional business plan, builds pipeline, leads strategic pursuits, and positions HPE data solutions for HPC and AI customers. Engages C-level buyers, partners, ISVs, GSIs, and channel teams; drives consultative sales, competitive strategy, forecasting, enablement, and revenue growth. Requires extensive storage solution sales experience, strong technical and commercial expertise, project management skills, and willingness to travel across the region.

Drive the end-to-end development of data products for Asset Management by translating business needs into requirements, coordinating data and technology teams, ensuring governance and quality standards, supporting adoption and value realization, and improving data product operating models. The role also evaluates existing products for duplication and consolidation opportunities while providing hands-on expertise across priority initiatives.

Lead software engineering initiatives for data platforms within an agile team. Provide technical guidance, develop and review secure production code, solve complex design and functionality problems, and influence application architecture and technical operations. Drive responsible adoption and governance of AI-assisted engineering tools, including code review, refactoring, testing, troubleshooting, and incident analysis. Serve as a subject matter expert, promote engineering standards, and contribute to firmwide software development practices.

Leads software engineering for a secure, scalable cloud data platform supporting credit risk technology. Responsibilities include designing and delivering Python solutions, reviewing production code, building CI/CD pipelines, improving application resiliency, standardizing SDLC tooling, automating remediation, and guiding responsible AI-assisted engineering practices. The role also evaluates vendors and leads cross-functional delivery initiatives involving AWS, Databricks, Spark, Terraform, lakehouse architecture, observability, security, and governance.

Lead infrastructure engineering for critical market data platforms: provide production support, implement changes, lead architecture and automation workstreams, validate AI-assisted recommendations, ensure performance, resilience and data quality, and collaborate across platforms to modernize and stabilize trading market data infrastructure.

Lead engineering of metadata, meta-modelling, and distributed systems; produce and review secure production Scala/Java code; drive adoption and governance of AI-assisted engineering across the SDLC; influence product design and operations; mentor technical teams; establish automation, validation standards, and reuse of proven patterns.