Data Scientist

About This Role

Working with data connected to services that millions of people and businesses across the UK rely on every day, this role applies solid data science practice in a clear, meaningful setting. You will help shape how the company uses data and AI across a trusted payments environment. The specialist will enjoy turning complex data into clear insight, practical models and well-structured analysis, working closely with colleagues across the organisation, using evidence to support decisions, improve understanding and help develop data capability in a way that is thoughtful, transparent and useful.

Responsibilities

• Analyse large and complex datasets to identify patterns, trends and risks relevant to Pay.UK’s services and operations
• Build, test and refine statistical and machine learning models that support better forecasting, monitoring and decision-making
• Prepare clear visualisations, reports and presentations that explain methods, findings and limitations in a straightforward way
• Work with colleagues across business and technical teams to define data questions, shape analytical approaches and agree practical outputs
• Translate business problems into structured analytical tasks, including data preparation, feature selection and model evaluation
• Improve data quality and analytical processes by documenting methods, validating outputs and supporting good data practice
• Use SQL and programming tools to extract, clean and transform data from multiple sources for analysis and modelling
• Support the development of Pay.UK’s wider data and AI capability by contributing to repeatable methods, standards and shared learning

Requirements

• Professional experience in a Data Scientist role, with responsibility for delivering analysis and predictive or statistical models
• Solid applied experience using Python and SQL to extract, prepare, analyze, and model data
• Solid grounding in statistics and machine learning, with the ability to choose and evaluate suitable methods for real business questions
• Experience presenting technical findings clearly to non-technical audiences through reports, visualisations or presentations
• Experience working with large, complex datasets and applying clear quality checks, documentation and validation methods

Benefits

• 12% Non-contributory pension
• Discretionary annual bonus
• 30 days annual leave (excluding bank holidays)
• Private medical insurance, life assurance, income protection, health cash plan, dental insurance, Bupa medicals etc
• Employee assistance programme
• Cycle to Work Scheme
• Season ticket loan
• Annual fitness subsidy of up to £500 per annum