Top Data Jobs in London

Design, build, and maintain large-scale data pipelines and distributed systems to ingest, process, and serve petabytes of vehicle data. Collaborate with ML and CV teams, mentor junior engineers, define long-term product strategy, and ensure robust, testable infrastructure using cloud and orchestration tools.

Own and build the integrated demand-forecasting models (D0–D30) that drive sorting, routing and network planning. Lead the hardest forecasting problems: long-horizon model generation, inbound international volume, parcel size/weight prediction. Define methodology, validation standards, model interfaces, and production quality while collaborating with ML engineers, analysts and operations to measure model impact on cost per parcel.

Lead hands-on delivery of data engineering engagements, build and mentor teams, set technical standards (testing, CI/CD, observability, governance), shape client proposals, represent YLD externally, and grow the data practice while stepping in on complex client work.

Lead strategic analysis, data governance and quality for a regulated payments platform. Synthesize multi-source data, define standards for modelling, visualisation and validation, influence stakeholders, and mentor analysts during transition on a 9-month fixed-term contract.

Serve as client-side electrical technical authority for data center projects: lead electrical design, manage external consultants, develop specifications, support construction and commissioning, drive standardized modular designs (DfMA), advise on OFCI procurement, conduct field investigations, and coach junior engineers while ensuring compliance with codes, IEC standards, and EU construction regulations.

Define and lead AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI. Lead and develop teams to deliver production-ready AI systems (LLMs, RAG, semantic search, embeddings), establish evaluation and responsible AI frameworks, and influence cross-functional stakeholders to align roadmaps and drive measurable product and business outcomes.

Lead data architecture and AI-enabled transformation projects for UK insurance clients: define architectures, govern data/AI, run metadata discoveries, assess data assets, support engineering delivery, and drive change management and adoption across multidisciplinary teams.

Build and optimise scalable, serverless data pipelines and storage on GCP. Implement ETL, CI/CD and DataOps practices, support model productionisation with data scientists, document architectures, and guide migration toward event-driven managed cloud services.

Build and lead the Data Labeling team, define annotation guidelines and QA frameworks, partner with researchers to create labeling workflows, prioritize projects, monitor metrics, improve tooling and automation, manage vendors, run complex AI evaluation projects (RLHF, safety, benchmarks), and communicate insights to leadership.

Lead or contribute to statistical programming for clinical trials, focusing on SDTM/ADaM datasets and TLFs. Oversee quality, validation, and dataset specifications, communicate with sponsors, and provide guidance on programming requirements. Oncology experience and team leadership are advantageous.

Manage clinical data activities for trials: design CRFs and databases, program/test edit checks, perform coding (MedDRA/WHO‑Drug), export CDISC SDTM datasets, generate queries, coordinate data entry and DB developers, support database lock and sponsor communication.

Lead canonical data modelling and governance for buy-side data domains, translating logical models into Snowflake-ready schemas, DDL, API contracts and data quality rules. Work with investment, operations and ESG teams to define lineage, golden sources, industry-standard mappings (ISO20022, SWIFT, FINOS CDM), and embed governance while mentoring engineers to ensure implementation fidelity.

Lead cross-functional engineering teams to design, deliver, and evolve cloud-native, event-driven insurance applications. Own architecture, roadmap, and delivery for policy, claims, underwriting, and compliance systems while ensuring regulatory adherence, vendor management, Agile/DevSecOps practices, and engineering KPIs.

Lead portfolios of marketing-mix-modeling (MMM) and marketing effectiveness programs, manage teams, ensure delivery quality, translate analytics into C-suite recommendations, drive account growth, and develop talent and practice thought leadership.

The Director of Business Development will drive revenue through creating strategies for new business, managing client relationships, and overseeing sales processes while ensuring high service standards.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

Lead a small team of pricing data scientists to own loss-ratio views, translate analytics into commercial pricing actions, drive cross-functional investigations with claims/finance/product, and communicate performance and risk trends to senior stakeholders to inform pricing strategy.

The Senior Data Scientist will develop predictive models, conduct statistical analysis, and work with cricket datasets to uncover trends and validate model performance.

As an Associate Director, you will lead HV substation design for data centres, manage technical discussions, ensure quality delivery, and mentor junior engineers.

The FP&A Analyst will translate financial data into management information, support budgeting, improve forecasting, and collaborate across departments to enhance the operating model.

The job involves designing, developing and testing data warehouse microservices, troubleshooting field issues, and collaborating with product and support teams.

The Senior Data Scientist will collaborate with product teams, develop metrics, design data pipelines, and influence product strategy through data analysis at Intercom.

As a Senior Data Scientist at Intercom, you'll analyze data to drive decisions, support product teams, build data pipelines, and influence product strategy using AI tools.

Design, implement, and maintain data lakehouse architectures on AWS; build secure data pipelines with PII protections and compliance; advise clients across technical and executive stakeholders; manage data residency requirements; collaborate with analytics, security, and legal teams; support ML feature stores and model deployment.

The Senior Data Analyst will support the CEO Office with analytical insights for transformation initiatives, evaluate market opportunities, identify growth areas, and develop analytical models for business performance.