Data Scientist

• Lead a team focused on helping Deliveroo acquire, onboard, support and retain merchant partners
• Identify high-value problems and guide the team's analytical approach
• Partner closely with senior stakeholders across Product, Engineering, Strategy, Operations and Commercial
• Maintain high analytical standards and support team development through coaching and feedback
• Shape the team's roadmap and influence senior stakeholders

Data Science Manager – Merchants Team

• Act as a subject matter expert, providing guidance on data protection and AI governance matters across the business
• Support and advise teams on Data Protection Impact Assessments (DPIAs), Privacy Impact Assessments and vendor risk assessments
• Assist with the investigation and management of data incidents and breaches
• Take ownership of Data Subject Rights Requests (DSRs), ensuring regulatory deadlines are met
• Maintain Records of Processing Activities (ROPAs), including new and AI-related processing activities
• Develop, review and enhance data protection and AI governance policies, procedures and guidance
• Review Data Processing Agreements (DPAs) and assess privacy and AI-related risks during procurement activities
• Design and deliver engaging training and awareness programmes across the organisation
• Support customer audits, due diligence questionnaires and assurance activities
• Manage and enhance the privacy programme management platform, identifying opportunities for continuous improvement

Data Protection Manager – FTC

• Leading quality, productivity and efficiency initiatives across data or technology-enabled processes.
• Using tools such as Power BI, advanced Excel or similar approaches to generate insight and support decision-making.
• Identifying opportunities to improve workflows, quality controls, data assurance and process performance.
• Supporting teams to test, implement and embed new systems, tools or ways of working.
• Carrying out productivity analysis, including time-and-motion studies, to identify where effort can be reduced.
• Tracking benefits, reporting outcomes and documenting process changes clearly.
• Working with stakeholders across teams to build confidence, alignment and momentum for change.

Productivity Lead – Operational Processes, Data and Technology

• Owning metric integrity — defining and governing what our numbers actually mean, so no one downstream is making a call off a flawed definition or a dodgy query.
• Acting as the quality gate on AI-generated analysis — checking the logic, validating the output, and catching errors before they ever reach a stakeholder.
• Designing and interpreting A/B tests — setting the success metrics, sizing the sample properly, and knowing when a result is underpowered rather than just running with it.
• Diagnosing what's actually driving commercial performance — why revenue is moving, where leads are dropping out of the funnel, which segments are underperforming — and turning that into a structured investigation with real hypotheses.
• Turning analysis into action — sizing the commercial impact, laying out the trade-offs, and helping the business decide what to do differently, then tracking whether it worked.
• Building interactive dashboards and self-serve tools that keep stakeholders oriented day-to-day, without an analyst needing to be in the loop every time.

Analytics Lead – Experimentation

• Own the vision and strategy for the UK Data Centres to realise the UK Portfolio vision of being a leader in sovereign services (Roadmap / Go to Market / Story) aligned to the overall UK Portfolio strategy
• Lead the development of a compelling Data Centre offering that is driven by demand from the wider portfolio (Uvance, Europe, Partner solutions and UK offerings).
• Oversee the lifecycle and roadmap for UK Data Centre offering ensuring they align to demand generated by other offerings and deliver clear desirability, business value and technical feasibility, from concept through to retirement
• Management of the stakeholder landscape for portfolio including global, Europe, and Partners for Data Centres
• Ensure the UK sales and delivery teams are enabled to sell and deliver relevant Portfolio offerings.
• Lead internal and external promotion of offerings, collaborating with marketing, sales and analysts.

Data Centre Strategy & Offering Manager

• Partner with stakeholders across the company to understand business priorities, identify opportunities to create measurable customer and business value, and develop data science roadmaps that support strategic objectives.
• Drive impactful outcomes for customers and the business by transforming complex data into actionable insights, recommendations and data products that enable objective decision-making with speed and confidence.
• Promote and champion a data-driven culture by applying advanced analytics, statistics, machine learning, AI, and emerging technologies to solve business problems, improve performance and help the organisation move from reactive reporting to proactive and predictive decision-making.
• Design, develop, deploy and continuously improve predictive, propensity and optimisation models that support customer acquisition, retention, cross-sell, customer lifetime value and margin optimisation.
• Challenge existing ways of working by exploring new methodologies, technologies and AI-driven capabilities, identifying opportunities to improve efficiency, scalability and business outcomes.
• Contribute to the evolution of the organisation's data platform, supporting the implementation and adoption of Microsoft Fabric and helping to establish modern, scalable and trusted data science, engineering and analytics capabilities.
• Work collaboratively with Data Engineering to identify, integrate and operationalise valuable internal and external data sources, ensuring high standards of data quality, governance, accessibility and trust.
• Support the design and development of data pipelines, APIs, data integrations and reusable data assets that enable advanced analytics, machine learning and self-service data capabilities within the Microsoft Fabric ecosystem.
• Create and maintain clear, high-quality documentation for models, methodologies, datasets and projects, ensuring transparency, reproducibility and effective knowledge sharing across teams.
• Work closely with Business Intelligence and Reporting teams to deliver intuitive dashboards, visualisations and data products that effectively communicate insights, recommendations and commercial impacts to technical and non-technical stakeholders.

• Support the development and implementation of a centralised data repository for renewable energy generation data
• Develop and maintain data governance standards and processes
• Support the definition of data ownership and stewardship responsibilities
• Work with business and technical stakeholders to understand and document data requirements
• Support the design, implementation and integration of data management solutions and associated systems
• Help improve data quality, consistency and standardisation across multiple data sources
• Support data migration, validation and ongoing data maintenance activities
• Contribute to the development of data models, metadata standards and reporting frameworks
• Support effective master and reference data management practices
• Work collaboratively with project, engineering, environmental and operational teams to improve the management and use of business-critical data
• Identify opportunities to improve data management processes and capabilities.

Data Manager

• Develop machine learning and AI systems that improve decisions across pricing, underwriting, portfolio management, operations, and claims.
• Work across structured data, text, documents, and external data sources, applying statistical modeling, modern machine learning, AI and agentic workflows to solve challenging real-world problems.
• Identify the right approach, build production-ready solutions, and measure the business impact of your work.
• Tackle a broad range of machine learning and AI problems such as predictive modeling, classification, ranking, matching, recommendation, anomaly detection, information extraction, entity resolution, building high-quality datasets, and automating analytical and decision-making workflows.

Principal Data Scientist – Machine Learning, AI

• Delivery oversight and accountability for digital products.
• Deliver projects, products, and services using appropriate management methodologies, while providing constant visibility of work in progress, planned work, and other key metrics.
• Effective collaboration with the Product Manager, Product Owner, Architects, and other key stakeholders to help shape the roadmap and ensure delivery of project goals.
• Manage the solution development budget, ensuring consistent delivery and excellent returns on investment.
• Lead work planning activities using collaborative and dynamic processes - prioritising the work that needs to be done against the capacity and capability of the team.
• Use appropriate quality assurance processes to ensure that all aspects of solution development are carried out in accordance with the agreed standards, methods, and procedures.
• Coach and maintain a high-performing, cross-functional team comprising solution SMEs, test analysts, business analysts, infrastructure engineers, and other technical specialists.
• Primary escalation point for the team, resolving impediments and working to continuously improve delivery, driving for consistent, predictable, high-quality deliverables.
• Lead supplier engagement for the delivery team, managing and building highly productive supplier relationships.
• Participate actively in the Delivery Manager community sharing skills, knowledge, and best practices.
• Stay current with your understanding of the fast-changing technology market and ensure we are aligned with current best practices.

Data Governance Delivery Manager

• Oversee the effective operation and continuous improvement of the Group’s HR and Payroll system to support business and employee needs
• Represent HR Data & Systems in cross-functional transformation programmes and strategic projects
• Lead on HR data and systems workstreams for annual processes such as the pay review and budgeting process
• Drive system upgrades and enhancements internally and with third party providers, ensuring successful delivery and adoption
• Proactively identify opportunities to increase automation and improve workflows
• Partner with colleagues on the management and enhancement of recruitment and training systems
• Lead the HR systems and people data workstream for mergers, acquisitions and business integration activity, acting as the subject matter expert for data migration, system integration and organisational structure design
• Develop and execute integration strategies to ensure the seamless transfer of employee data and successful onboarding of acquired businesses into Group HR systems
• Own the governance, delivery and continuous development of data integrity processes to ensure people data is accurate and compliant with legal and GDPR requirements
• Lead complex and large-scale data updates, uploads and migrations, proactively identifying and managing risks and ensuring deliverables are met
• Own the governance, delivery and continuous development of people reporting and analytics
• Own the development of workforce analytics, providing insight and commentary on trends, risks and opportunities and actionable recommendations that support business planning and decision-making
• Accountable for the performance, development and management of the HR Data & Systems team, ensuring delivery of agreed priorities, projects and operational objectives
• Set and monitor team quality standards for reporting, data and system processes
• Champion and role model a culture of collaboration, inclusion and continuous improvement
• Manage relationships with third-party providers to ensure issues as resolved in a timely way, monitoring resolution against SLAs and escalating where necessary
• Build strong relationships with HR, Payroll, Finance, IT, and business teams, providing expert support as needed
• Understand and translate business needs into reporting and system solutions

HR Data & Systems Lead

• Lead key data and analytics initiatives, including the Enterprise Data Lake, BI platform, and Data Governance framework
• Ensure all project objectives are met within scope, budget, and timeline
• Develop and maintain detailed project plans, including schedules, resource allocation, risk management, and communication strategies
• Establish and maintain a robust enterprise-wide project governance framework
• Act as the primary interface with vendors delivering data platform components
• Oversee vendor performance, ensuring compliance with SLAs and contractual obligations
• Build strong relationships with senior business stakeholders and technology teams
• Monitor project progress, proactively identifying and mitigating risks
• Deliver the implementation of the enterprise data governance framework

Data Delivery Project Manager

• Responsible for the technical development and leadership of AI/ML projects from initial idea scoping right through to final project delivery both in customer and internal domains.
• Demonstrate novel thinking and propose new ideas for solving challenging problems while mentoring others on your project team to deliver towards your proposed solution.
• Develop complex, novel data science solutions, contributing significantly to machine learning projects with minimal guidance.
• Undertake research and applied AI/ML tasks on both customer and internal research projects.
• Generate ideas for new research directions and provide technical leadership in small project groups.
• Work with customers and internal stakeholders, with varied technical knowledge, to determine appropriate technical approaches and do the technical development required for delivery.

Senior Data Scientist, Machine Learning Researcher

• Working as part of the Global DPO Office to provide practical, proportionate data protection advice, oversight and challenge across the bank.
• Reviewing DPIAs, providing DPO opinions, assessing data breaches, and supporting clear, well-documented decisions on regulatory reporting.
• Supporting our relationship with regulators, improving the processes behind regulatory engagement and complaints, and providing oversight of data subject rights and contact point processes.
• Supporting on and leading projects within the Global DPO Office at pace, and representing the team in projects led by others where data protection compliance is affected.
• Working toward specific goals and workstreams within the DPO Office maturity plan, working with the DPO and wider team to build practical, scalable and efficient processes, governance and ways of working.
• Proactively finding opportunities to improve how we work, including through better use of data, automation, AI and other tools that help us move faster without lowering standards.
• Deputising for the DPO from time to time, giving you the opportunity to build experience across DPO-level responsibilities.

Data Protection Manager

• Establish and evolve the operational analytics framework for new international markets, ensuring scalable measurement, reporting, and decision-making capabilities as we expand globally
• Operate with a business owner mindset by proactively identifying opportunities through analysis and product sense to enhance user experience, growth, and profitability
• Own business problems from end to end by translating analytical insights into recommendations and optimization strategies that support business growth, profitability, and operational excellence
• Take ownership of the end-to-end analytics process: define success metrics, generate insights and hypotheses, track performance, and create intuitive dashboards and reports that can be easily shared across the organization
• Develop scalable analytics solutions and data models
• Tackle ambiguous problems by identifying the core hypotheses and designing actionable experiments to validate product-market fit and economic viability
• Translate analytical findings into clear and compelling narratives and business cases for leadership to inform decision-making
• Spearhead weekly cross-functional metric reviews, collaborating with partners to conduct deep dives into significant metric shifts and suggest actionable steps
• Partner effectively across Product, Risk, Finance, Commercial, and Operations to align strategies and execute against business objectives
• Foster strong cross-functional relationships and establish yourself as a trusted advisor to team members
• Mentor and guide junior analysts to deliver high-impact work that drives business results

Analytics Lead – Full Stack

• Define and deliver the data and analytics strategy for combating fraud and financial crime
• Lead the end-to-end analytics lifecycle
• Drive measurable reductions in fraud risk through data-led decisioning
• Translate strategic priorities into scalable solutions
• Maintain strong governance and regulatory compliance
• Strengthen the Hub's analytics capability through leading practices

Analytics Lead

• Lead Data Science and AI capabilities for the Economic Crime Hub
• Design, build, and scale production-grade models and AI systems
• Own end-to-end lifecycle of models and AI agents
• Collaborate with Analytics, Product, and Technology teams
• Establish and enforce standards for model development and MLOps
• Build and lead a multi-disciplinary Data Science capability

Data Science Lead – AI

• Coordinate all the Configuration Management activities within your project(s)
• Organise the Configuration Management activities
• Establish and implement the Configuration Management Plan
• Specify the configuration management requirements to subcontractors and suppliers
• Ensure identification activities piloting and implementation
• Organise, lead and control the Configuration Control Board as well as the pre and post CCB activities
• Establish the configuration baselines
• Participate in end of phase reviews
• Perform or participate in Functional and Physical configuration audits
• Support in the analysis of contractual requirements

Configuration and Data Manager

• Define and maintain the end-to-end procurement analytics strategy, setting the direction for how we use data and market intelligence across value, risk, compliance, and supply market dynamics.
• Own the procurement data architecture, defining data domains, quality standards, and lineage to ensure analytics requirements are embedded upstream into process and system designs.
• Build a systematic external scanning capability combining macroeconomic trends, commodity cost drivers, and ESG data to generate practical, category-relevant insight and scenarios.
• Shape the procurement insight narrative for senior leadership and ExCo, producing robust, executive-ready reporting on performance, value delivery, and outlook.
• Sponsor advanced analytics capabilities—including should-cost, TCO, and business case modelling—partnering with Digital & AI teams to embed analytics into daily workflows.
• Act as the primary interface to Finance and enterprise analytics functions, ensuring performance and risk reporting is trusted, consistent, and aligned across the global matrix.

Head of Procurement Analytics, Insights

• Develop and execute a strategic plan for partner pursuits, aligned with Harvey’s overall product and GTM strategy.
• Independently identify, evaluate, and establish a range of partnerships to enhance product functionality and GTM motions.
• Negotiate complex partnership agreements, ensuring mutually beneficial terms and alignment with company goals.
• Conduct quantitative analysis, create business cases, and present them to executives.
• Collaborate closely with product, finance, legal and GTM teams to oversee the successful integration of new partners.
• Build and nurture strong long-term relationships with key partners, ensuring mutual success and achievement of partnership goals and business objectives.
• Operate autonomously, being both a proactive executor and strategic thinker.

Corporate Business Development Manager, Data

• Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products.
• Develop contextualized feature sets using specific domain knowledge in soccer.
• Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models.
• Strive to constantly improve model performance using insights from rigorous offline and online experimentation.
• Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts.
• Adhere to software engineering best practices and contribute to shared code repositories.
• Document modeling work and present to stakeholders and other technical and non-technical partners.

Data Scientist jobs in United Kingdom

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