Lead development and validation of internal risk models including PD, approval optimisation, propensity/conversion models, and internal scorecards
Build scalable modelling datasets using bureau data, application, repayment, and alternate data signals such as device metadata, user journey behaviour, and digital footprints
Partner with Product, Engineering, and Analytics teams to integrate models into production decisioning systems.
Build model documentation such as BRDs, methodology notes, validation reports, and monitoring dashboards.
Mentor junior data team members and guide analytical best practices.
510 years of experience in credit risk model development and validation with experience in personal loans, consumer lending portfolios, or unsecured credit.
Proficiency in Python, SQL, and ML/statistical modelling techniques.
Hands-on experience with bureau data and alternate data sources.
Strong analytical and problem-solving skills.
Qualifications
Master's degree in Statistics, Mathematics, or related field.
Experience in multi-lender decisioning or credit marketplaces.
