Top Data Jobs in London

Lead Real-World Data sales across EMEA by developing senior client relationships (Pricing, Market Access, HEOR, Medical Affairs), managing key accounts and operations, supporting the full sales cycle, aligning with global teams, shaping thought leadership, and delivering CRM-driven sales updates.

Lead delivery of technology, data platforms, and analytics across the investment lifecycle. Drive strategy execution, enterprise prioritisation, governance, and value realisation to enhance investment decision-making, client engagement, and commercial growth within a regulated asset management environment.

Design, implement, and operate large-scale distributed data systems and pipelines (batch and streaming) to power blockchain intelligence products. Drive technical decisions, improve reliability and observability, mentor engineers, collaborate with cross-functional teams, and adopt cloud-native and IaC tooling to optimise performance, scalability, and cost-efficiency.

Design, build, and optimise large-scale distributed data pipelines for blockchain and off-chain datasets using Scala, Spark and cloud technologies. Collaborate with engineers, data scientists, and product teams to deliver scalable, reliable ingestion and transformation workflows, improve pipeline observability and automation, and contribute across the data platform lifecycle.

Lead data reliability and SRE practices across engineering to ensure high availability and quality of enterprise-grade datasets. Build data-quality frameworks, observability, alerting and remediation; define SLAs/SLOs; run on-call rotations and incident command; produce post-mortems; report availability/performance; and embed DRE practices with product, sales, and customers.

Senior leadership role accountable for delivering technology, data and analytics across the investment lifecycle. Owns data platforms, data engineering, analytics enablement and enterprise prioritisation, governance and value realisation to enhance investment decision-making, client engagement and commercial growth within a regulated financial services environment.

Lead architecture and delivery of cloud data platforms, designing batch and streaming pipelines, data models, and governance. Advise executives, integrate LLMs/AI and MLOps, modernise AWS/Azure/GCP infrastructure, shape technical strategy, and mentor multi-squad teams to deliver business-focused data and AI solutions.

Lead enterprise data initiatives by translating data strategy into programmes, implementing governance frameworks, improving data quality and reporting, engaging global stakeholders, and ensuring data solutions meet enterprise standards to enable data-driven decisions.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Prepare, validate, cleanse and deduplicate voter data; allocate/manage voter credentials; maintain audit trails; perform QA, reconciliation and reporting; escalate data issues and follow data protection and security controls.

Lead and grow a regional Go-to-Market practice for technology solutions by defining strategy, owning solution portfolios, driving demand and sales, managing budgets and teams, creating roadmaps, enabling delivery through CI/CD and tooling, conducting solution design reviews, and fostering a community of practice to ensure profitable, scalable solution delivery.

Develop, validate, and deploy machine learning and statistical models for soccer betting products. Create soccer-specific features, run offline and online experiments, collaborate with data engineering and product teams, follow software engineering best practices, document work, and present findings to technical and non-technical stakeholders.

Own and grow a global portfolio of data and vertical-AI partners to drive pipeline, partner-sourced revenue, co-innovation, co-marketing, and co-selling. Build joint value propositions and multi-year partner roadmaps, enable data integrations with Celeste (via MCP and agent integrations), manage executive relationships, engage in sales opportunities, embed partner plans into business units, and report partner outcomes while working cross-functionally and traveling as required.

Develop, backtest, operationalise and trade American Football quantitative strategies (pre-match and in-play). Set and adjust pricing, monitor models live, manage risk, collaborate with quants and engineers, and support data acquisition and cleaning.

Lead enterprise Data, Analytics and AI product strategy and portfolio, driving solution design, delivery, governance and lifecycle management. Coach solution designers, manage vendors, ensure platform reuse (including SAP integration), and deploy responsible Generative and Agentic AI solutions while partnering with governance, data quality and business stakeholders to realize measurable value.

Work directly with clients to build modern data and analytics capabilities: redefine reporting on Kraken data, coach client teams on best practices, provide occasional SQL/BI examples, translate client needs to product/engineering, and train delivery teams.

Provide specialist data privacy legal advice on UK GDPR, Data Protection Act 2018 and PECR; draft and negotiate privacy provisions in commercial and outsourcing contracts; advise on international transfers and AI initiatives; collaborate with Legal, Compliance, InfoSec, DPO and business stakeholders to ensure privacy governance, training, templates, and compliance across Santander UK.

Operate the product data layer: respond to data requests, pull/shape/import data, validate and QA datasets, run ingestion tasks, use AI tools to accelerate SQL/NoSQL queries, document sources and queries, and partner with engineers and product to keep data reliable and accessible.

Design and build predictive machine-learning models and features from raw telematics data to predict claims, fraud and risk KPIs. Collaborate with ML Engineers to deploy and monitor models, link model performance to commercial outcomes, present results to stakeholders, and explore new technologies and best practices.

Design, build and deploy machine learning models and novel telematics-based features to predict claims, fraud and risk KPIs. Collaborate with ML Engineers to productionize and monitor models, present findings to commercial and operational stakeholders, and contribute to team best practices and technology exploration.

Monitor YouTube, podcast charts and social platforms to identify emerging guests and trends. Pull and analyze performance data using analytics tools, build a living knowledge base of creators, surface data-backed guest recommendations, and support pre-production with research and competitor insights to inform booking decisions.

Perform advanced data analysis on large consumer credit datasets using SQL and Python; extract, transform and analyse data; develop innovative analytical approaches; produce clear written and visual outputs to inform regulatory decision-making; collaborate with stakeholders and contribute to an experienced analytics team to deliver insight across consumer finance.

Support development and implementation of data quality methodologies, cleansing solutions, and dashboards. Perform data analysis, define metrics, report improvements, and help stakeholders resolve data quality issues while promoting data governance across the organisation.

Lead and grow a London-based AI & Data engineering team to build and productionise data and agentic AI platforms for trading, risk and quant workflows. Deliver scalable data pipelines, cloud-native infrastructure, vector/knowledge-store based AI solutions, governance, and front-office integrations while partnering with Traders, Quants, Risk, and Compliance to drive measurable business impact.

Lead technical pre-sales engagements for Databricks, demoing Spark and data/AI solutions, building architectures, authoring reference materials, and collaborating with account teams to design and deliver customised proofs-of-concept and workshops.