Top Data Jobs in London

The Director of Colleague Data Science & Analytics will lead the global HR analytics function, driving innovative solutions to support decision-making and enhance the colleague experience.

The Data Solution Architect will design and implement cloud-based data and AI platforms, ensuring scalable data solutions and effective communication with clients.

The Data Engineer will implement cloud-native data platforms, engineer scalable pipelines, and optimize cloud resources using Python and SQL, while applying agile methodologies and cloud automation tools.

As a Senior Data Analyst, you will gather and document business requirements, manage stakeholders, analyze complex datasets, and create data models and dashboards.

As Lead Data Analyst, you will monitor and ensure the accuracy of forecasting models, diagnose forecasting errors, and communicate findings to stakeholders for operational improvement.

Design and deliver statistical, probabilistic and simulation models to support decision-making. Translate business questions into deployable analytical solutions, quantify uncertainty, validate and monitor models, and partner with engineering, product and business teams to productionise models and define operational requirements.

Lead clinical data harmonization for the STELA program: map partner clinical sources to ontologies, design data dictionaries and QC pipelines, write reproducible Python code to clean and validate multimodal clinical datasets, and collaborate with external hospitals/CROs to standardize data for AI model training, with emphasis on oncology and immunology.

The Data Management Lead defines data strategy and architecture for telecom data, aligning it with AI and automation, while driving product innovation and implementing scalable solutions.

Partner with Product and Engineering to define metrics, run root-cause analyses and experiments, build tracking, reporting, and automated alerts, model data in dbt/BigQuery, scale AI-assisted analytics for self-serve, and communicate insights to drive product and business decisions.

The Senior Data Engineer will design and build data pipelines on GCP, ensuring high data quality and reliability for analytics and ML products. Responsibilities include mastering ETL processes, managing workflows with Airflow, and collaborating closely with ML engineers.

Define and lead LLM discovery and optimisation strategy across SEO and AI-driven platforms. Monitor generative AI/search developments, translate trends to strategy, run measurement and experimentation linking visibility to business outcomes, and partner cross-functionally to embed AI discovery insights. Specify technical, content and authority signals for generative responses and establish governance, best practices and capability-building.

Lead technical delivery of physical security design for EMEA data centres: develop and standardize security systems (access control, VMS, PIDS, cabling, PSIM), review consultant designs, support site selection and project phases, run technical workshops, ensure compliance with standards, and provide stakeholder technical authority and innovation.

Lead development and productionisation of scalable AI models and data-driven solutions. Tune and optimise models, evaluate third-party AI tools, define coding standards, and collaborate with software engineers to deliver high-quality, maintainable production systems aligned with business goals.

Lead and grow the data engineering team, own technical strategy and delivery roadmap for scalable data infrastructure, partner with cross-functional leaders to prioritise data work, and drive AI-led development while remaining hands-on to ensure solutions deliver business results.

Provide legal advice on data and technology matters, develop and implement data policies (retention, deletion, storage), prepare guidance and training, advise on cross-jurisdictional data/privacy law issues, support practice groups and business services, and work with the AI Governance team to create standards and processes for data use in AI systems.

Lead customer underwriting proof-of-concept projects using SQL, Python, and AWS to transform, validate, and deliver insurance risk data. Match address data to reference identifiers, investigate data-quality issues, document outputs, support underwriting data platforms, and automate manual workflows. Collaborate with technical and non-technical stakeholders, communicate project updates, and improve scalable data processes, quality, and customer experience.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, RAG, hybrid search, and agentic workflows. Analyze large-scale intellectual property datasets, design experiments, evaluate and benchmark models, define reasoning strategies, and translate findings into product recommendations. Collaborate with product managers, IP experts, and engineers to deliver scalable, customer-facing solutions.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, generative AI, retrieval, and hybrid search. Define multi-step reasoning workflows, analyze large-scale intellectual property datasets, establish model evaluation and benchmarking practices, and translate experiments into product recommendations. Collaborate with product teams, intellectual property experts, and engineers to deliver scalable, customer-facing solutions.

Leads complex machine learning delivery and Defence-sector strategy, translating client challenges into technical roadmaps, scoping projects, managing client relationships, and supporting technical sales. Writes production-grade Python, serves as a machine learning authority, develops Generative AI and agentic AI solutions using LLMs, and mentors and manages data scientists.

Lead Moonfare's data strategy and execution, unifying Data Engineering and Analytics into a cohesive team. Build scalable data platforms, pipelines, governance, and compliance-ready architecture to support investment, investor relations, operations, and AI initiatives. Partner with Engineering, Product, and executives while contributing hands-on to technical design and delivery.

Design, build, and maintain scalable data pipelines and infrastructure using Python and Snowflake. Deploy and orchestrate data services on Kubernetes, implement CI/CD with GitHub, ensure data quality, observability and security, collaborate with engineering and data science, and support ML model deployments and platform reliability.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Lead design and delivery of production-grade AI/ML solutions for Kainos Workday products. Build predictive analytics, anomaly detection, generative AI features, and scalable MLOps pipelines. Integrate with Workday, mentor and line-manage a data science team, manage client engagements, and drive architectural and technical leadership across product initiatives.

Lead discovery, definition and delivery of data-focused products. Create roadmaps, user stories, wireframes and technical specs. Run Agile ceremonies, prioritise backlog, resolve stakeholder conflicts, manage delivery to budget and timeline, support adoption, and collaborate with engineering, QA, design, data analysts and cross-functional stakeholders.

Lead enterprise data management strategy and execution, strengthening governance, data quality, controls, accessibility, automation, and AI-enabled capabilities. Build and lead high-performing teams, align stakeholders across business, technology, risk, and compliance, manage budgets, and drive large-scale transformation to deliver measurable business value in a regulated environment.