Top Data Jobs in London

The Lead Value Engineer is a trusted advisor to customers, driving their value journey through analytics, process improvement, and stakeholder engagement, particularly in Finance and Supply Chain.

The Partner Program Manager will design and manage a tiered partner program, focusing on value-added systems for partner rewards, enablement, and performance analytics.

As an Enterprise Architect, you will lead tech advisory growth, collaborate on solutions, manage client relationships, and mentor junior consultants within the organization, driving technology transformation for clients.

Lead complex engagements in Life Sciences Consulting, managing project teams and relationships, driving strategy and financial outcomes, while fostering a culture of excellence in the team.

The role involves shaping data and AI strategies for financial institutions, guiding clients in harnessing AI for competitive advantage, and leading workshops to align stakeholders.

Lead analytics for customer operations: build capacity planning and forecasting models, own data pipelines, develop predictive and causal inference analyses, track KPIs, standardise processes, and partner with operations, WFM, quality, and training to drive data-driven improvements.

Lead analytics for FinCrime operations: build capacity-planning and forecasting models, own data pipelines, develop predictive and causal models, track KPIs and initiative performance, conduct cost and operational health analyses, and standardise processes with stakeholders to optimise operations.

Drive analytics for Payment Operations to improve payment quality and efficiency. Build attribution models for quality lapses, incorporate AI into review processes, expose and visualise payment data, create reports and pipelines, track KPIs, and collaborate with senior stakeholders to turn insights into operational improvements.

Lead analysis of operational data to support decision-making. Build dashboards and reports, partner with operations stakeholders to identify process improvements, monitor KPIs, and inform strategic initiatives.

Senior Data Scientist embedded in international teams to ingest, validate, and transform partner oncology data into research-grade datasets. Build and automate scalable pipelines, apply ML/LLM techniques to unstructured EHR data, and collaborate with cross-functional stakeholders to develop and deploy real-world data products.

The Senior Data Scientist will lead the delivery of data science solutions, mentor teams, and develop ML models to address business challenges.

You'll partner with senior leaders to define and improve reliability metrics, influencing decisions based on data insights and system performance.

As a Lead Data Scientist, you will develop algorithms to combat financial crime, collaborate with teams, and engage in product design and prototyping using payments data.

Build and maintain ultra-high-scale data platforms and pipelines (petabyte scale). Write fault-tolerant Java/Spark code, design low-latency query capabilities, improve performance and stability, participate in technical reviews, and enable customers/internal teams to query and extract analytics from event data.

The role involves designing and maintaining a data platform, enhancing system efficiency, implementing data query solutions, and technical reviews within a data engineering team.

The Engineering Manager will lead a Data Replay & Recovery Team to build a data replay application, improve service efficiency, and design a data platform for processing large datasets.

Design, build, and operate highly scalable real-time streaming microservices and data pipelines (Java/Python/Go) using Kafka, Flink/Spark on Kubernetes across multi-cloud and on-prem. Own design, deployment, monitoring, observability, and on-call support while improving platform reliability and developer experience.

Serve as the primary data consultant for a business domain, translating stakeholder needs into prioritized data product requirements, conducting lightweight ad-hoc analysis (SQL, Looker), triaging requests, tracking business value and ROI, and enabling teams to self-serve while ensuring data quality, adoption and measurable impact.

Lead data analysis and strategy for the customer organisation. Build KPIs, dashboards, forecasts, and models; identify growth opportunities and risks; run executive presentations and business reviews; own annual budgeting/planning; improve data processes and drive a data-driven culture.

Lead and scale multi-team AI engineering and data science organization to design, deliver, and govern GenAI, LLM, Vision AI, and multi-agent knowledge products; own end-to-end solution design, Agile delivery, quality standards, production validation, stakeholder alignment, hiring, and organizational capability building.

The Senior Marketing Data Analyst will maintain the attribution model, ensure data accuracy, work with marketing and data teams, and provide insights to improve marketing effectiveness.

Lead the AML Risk Data Science team to develop machine learning solutions for detecting financial crime, optimize performance, and mentor team members.

The Staff Data Analyst leads complex projects, develops scalable data solutions, and mentors other analysts while driving strategic initiatives at Wise.

As a Data Management Consultant, you'll design and implement modern data management frameworks, support AI-enabled solutions, and drive adoption through stakeholder collaboration.

The Senior Data Platform Engineer will manage Databricks infrastructure, develop cloud systems, collaborate with teams, and enhance machine learning workflows.