Salary: £50,000 - 55,000 per year Requirements: Proficient in SQL for querying, joining, and transforming large datasets. Experienced in data cleansing, validation, and predictive modelling. Strong in Python for statistical analysis and able to communicate insights to non-technical stakeholders. Proven experience in credit risk analytics, debt management, or financial modelling. Comfortable working cross-functionally and translating data into actionable strategy. Familiarity with cloud platforms such as Azure, AWS, or Google Cloud. Degree (or equivalent) in Data Science, Mathematics, Statistics, or a related field. Experience migrating from traditional databases to data lake architectures (desirable). Background in Financial Services or other regulated industries (desirable). Exposure to SAP/DM9 environments (desirable). Knowledge of machine learning techniques relevant to credit risk (desirable). Responsibilities: Conduct root cause analysis of debt accumulation trends. Build and refine predictive models for credit risk and debt recovery. Develop and maintain SQL-based reporting solutions to drive actionable insights. Collaborate across teams to align data governance, infrastructure, and reporting needs. Embed analytics into strategic decision-making and champion data-driven thinking. Technologies: AWS Azure Cloud Machine Learning Python SAP SQL Support More: We are a dynamic Credit Risk function offering a unique opportunity to work at the forefront of credit risk analytics, helping to shape smarter collections strategies, reduce bad debt, and improve outcomes for customers. We provide hybrid working flexibility in the South West, a competitive salary of up to £54,000 per annum plus benefits, and opportunities to work on high-impact projects that shape strategy and operations. If you are passionate about using data to drive decisions and make a difference, wed love to hear from you. last updated 6 week of 2026