Leads pre-funding credit decisioning strategy for hire purchase lending, including policy rules, score cut-offs, performance monitoring, back-testing, governance, and production deployment. The role evaluates approval rates, losses, yield, and profitability while collaborating with fraud, affordability, data science, product, and engineering teams. It manages two analysts, develops reusable Python tools, coaches the team, presents recommendations to senior stakeholders, and incorporates AI into analytical workflows.

Develop and deploy Python and SQL-based data science models for credit risk, pricing, loss forecasting, collections, and automated loan decisioning. Responsibilities include exploratory analysis, model validation, production deployment, testing, documentation, monitoring, governance, and stakeholder communication. The role partners with credit, pricing, operations, product, engineering, and data teams to deliver interpretable, technically rigorous solutions.