Top Data Jobs in London

Provides senior technical leadership for enterprise data architecture and delivery across Google Cloud engagements. Designs scalable data platforms, pipelines, models, integrations, governance, security, and observability solutions; supports hands-on implementation; develops technical estimates and proposals; partners with cloud, data, and AI teams; establishes architectural standards; mentors engineers; and contributes to client solutioning and pre-sales activities.

Six-month Data Science and Marketing Effectiveness internship analyzing large datasets, building marketing mix models, forecasting tools, customer segmentation, and econometric or machine learning models. The intern will use Python and related analytics tools, translate findings into client recommendations, participate in consulting projects, and complete an individual R&D project. The role is hybrid in London and requires full UK work authorization without sponsorship.

Leads end-to-end business analysis for AI, automation, and data initiatives within the tax technology function. Responsibilities include stakeholder workshops, requirements gathering, process analysis, user stories, acceptance criteria, backlog refinement, traceability, dependency and risk management, solution alignment, and UAT planning and execution. The role bridges tax business stakeholders with product, architecture, delivery, and testing teams to ensure technology solutions meet agreed business needs.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Leads measurement strategy across PlayStation by designing experiments, causal inference methodologies, statistical models, and machine learning solutions. Establishes experimentation best practices, influences platform capabilities, partners with product and business leaders, communicates analytical recommendations, and mentors data scientists and analysts. The role provides technical leadership for evidence-based product and commercial decisions affecting millions of players.

Lead WAM data architecture and cloud transformation engagements: define enterprise data strategies, design canonical WAM data models, architect cloud-native data platforms, integrate core WAM systems, establish data quality and control frameworks, and advise senior stakeholders on technical-to-business translation.

Senior Consultant serving as a business-facing reinsurance data analyst in a consulting environment. The role analyzes reinsurance data structures, definitions, and flows; translates business needs into data requirements; validates data using SQL and Python; and supports data products, analytical datasets, and transformation initiatives. It requires strong reinsurance knowledge, stakeholder management, consulting skills, and collaboration with engineering and architecture teams.

Leads consulting engagements for insurers and reinsurers, translating business strategy into data- and AI-enabled operating models, capability maps, transformation roadmaps, semantic models, and structured solution designs. The role facilitates workshops, aligns business and technology stakeholders, assesses data landscapes, identifies AI opportunities, supports implementation teams, and develops reusable data and AI proposition assets. It requires strong insurance domain knowledge, business architecture, data modeling, analytical, communication, and consulting capabilities.

Leads the technical direction of data engineering, owning scalable pipelines, warehouse architecture, data models, ELT transformations, quality monitoring, and platform reliability. Defines engineering standards, reviews designs and code, drives CI/CD and observability, resolves complex technical issues, and mentors engineers. Collaborates with analytics, reporting, data science, and platform teams to translate requirements into performant, cost-effective solutions while contributing to warehouse modernization and technical planning.

Lead and grow a team of ML engineers to build and operate production ML and LLM systems—real-time inference APIs, batch data products, and agentic AI—ensuring deployment, monitoring, CI/CD, reproducibility, and measurable business impact.

Design, develop, deploy, and monitor machine learning and AI models, including predictive models, NLP, computer vision, and generative AI solutions. Analyze and transform large datasets, build scalable data pipelines, automate ML workflows, evaluate model performance, and integrate models into production. Collaborate with technical and business stakeholders to deliver actionable insights and continuously improve AI products.

The Data Analyst will leverage data to provide insights, automate reporting, improve customer/vendor experiences, and help reduce returns costs at Quince.

Lead index and benchmark data management across the product lifecycle: own data quality, governance, cataloging, documentation, and risk. Partner with product, technology, and business teams to drive data-driven product innovation, ensure compliance, and promote data literacy while leveraging AI and cloud platforms.

Lead design, delivery and maintenance of on-prem and cloud market-data distribution systems (real-time, historical, AI/ML use cases). Collaborate with product/stakeholders, provide 3rd-level operational support, validate AI-assisted recommendations, ensure resiliency, security, auditability and strong process controls.

Lead design and delivery of cloud-native data and AIML production systems. Build data engineering, backend, Cloud infra/DevOps and MLOps stacks, produce secure production code, architect microservices and distributed, data-intensive applications, and drive adoption/governance of AI-assisted engineering practices while communicating with stakeholders.

Lead design and delivery of high-performance, real-time data pipelines and analytics for trading. Drive AI-enabled data engineering, mentor engineers, manage global initiatives, and improve SDLC, testing, and operational reliability.

Design, build, and operate cloud-native lakehouse and streaming data platforms and pipelines using Python, PySpark, dbt, Airflow, and orchestration/infrastructure tooling. Ensure performance, reliability, security, and observability; model and transform data for analytics; deploy with IaC, containers, and Kubernetes; mentor engineers and drive platform standards and best practices.

The Managing Consultant will lead data science initiatives, drive business growth in financial services, and build client relationships while managing teams and delivering high-impact solutions.

Drive the go-to-market strategy for EMEA Financial Services, focusing on Banking, Capital Markets, and Insurance. Develop relationships, execute growth plans, and engage in thought leadership.

Lead national business development for JDP’s UK data centre sector. Build relationships with developers, operators, consultants, contractors, and supply chain partners; secure product specifications and project opportunities; convert new business; manage the project pipeline and sales forecasts; and represent the company at industry events. The role sells drainage, ducting, cable protection, water management, and infrastructure solutions.

Leads a 25+ person organization of data scientists, machine learning engineers, and analytics engineers across Identity and Financial Crime. Owns data quality, governance, lineage, observability, fraud and financial-crime models, production performance, monitoring, retraining, and domain data products. Partners with engineering, product, risk, compliance, legal, and central data teams; influences upstream teams, develops managers and senior ICs, handles incidents, and scales hiring and technical strategy.

Lead the design and delivery of enterprise data architectures, strategies, governance frameworks, cloud platforms, and analytics solutions for defence, government, and regulated-sector clients. Responsibilities include stakeholder engagement, requirements analysis, architecture documentation, technical governance, project lifecycle leadership, business-case development, and support for proposals and customer presentations. The role also contributes to data capability development, emerging technology evaluation, and AI-enabled transformation.

Develop statistical and machine learning models using soccer tracking and event data to support player recruitment decisions. Build spatio-temporal models, metrics, analyses, and interpretation tools; validate models; communicate findings to professional club clients; and partner with engineering on cloud deployment and production reliability. The role also includes code review, model maintenance, and advancing analytical methods.

Leads electrical design for hyperscale and mission-critical data centers across Europe. Responsibilities include managing HV/MV/LV systems, substations, utilities, consultants, permitting, project delivery, construction support, commissioning, and integrated systems testing. The role provides client-side technical leadership, reviews designs and project documents, coordinates multidisciplinary teams, manages risks and milestones, and ensures compliance with standards and operational requirements.

Develops and maintains centralized financial datasets supporting management P&L, balance sheet substantiation, statutory reporting, and AI-enabled finance tools. Builds reconciliations to the general ledger, partners with data engineering and IT teams, leads UAT, documents datasets and tools, trains Finance users, and supports migration to IT-owned platforms. The role requires strong regulated-finance experience, advanced Excel skills, control expertise, and familiarity with financial products and data-manipulation tools.