• Located in Maidenhead
• Reporting to Head of Business Intelligence 

Job Overview

The Data Scientist is responsible for designing, developing, scaling, and maintaining advanced analytics and machine learning solutions for the affiliate. The role translates business questions into robust analytical frameworks and predictive or prescriptive models that improve decision-making and deliver measurable business value.

Working across business and technical teams, the Data Scientist partners with stakeholders to define use cases, requirements, timelines, and success criteria, and supports the deployment of scalable, compliant, and sustainable analytics solutions. The role combines strong technical capability in data science, statistics, and programming with business acumen, communication skills, and a practical delivery focus.

Key Responsibilities

Advanced analytics and modelling

• Design, develop, deploy, and maintain predictive and prescriptive models to address affiliate business needs.
• Translate commercial problems into mathematical, statistical, and analytical approaches.
• Apply machine learning and advanced analytics methods to solve complex business challenges.
• Build reliable, scalable, and modular solutions using datasets of varying quality and completeness.
• Maintain, optimise, and refresh existing models to ensure continued performance and value.

Business partnering and delivery

• Partner with stakeholders to define business questions, requirements, timelines, objectives, and success criteria for data science initiatives.
• Work closely with Business Analysts, Data Analysts, BTS, and technical partners to move solutions from concept or pilot into production.
• Ensure projects are delivered on time, accurately, within budget, and in line with compliance and governance requirements.
• Support validation, user acceptance, and effective handover of solutions to business users and partner teams.
• Contribute to the deployment of global and affiliate-led analytics, automation, and AI initiatives.

Communication and impact

• Communicate model logic, assumptions, outputs, and business implications clearly to technical and non-technical audiences.
• Translate complex analyses into clear, practical recommendations for decision-makers.
• Use effective visualisation and storytelling approaches to support understanding and action.
• Build strong working relationships across business and technical teams, establishing credibility through technical rigour and business relevance.