Johannesburg: Graduate Actuary / Data Scientist

Join a specialist credit and collections environment where data is at the centre of strategy . In this role, youll build the single source of truth for active DR, pre‑Term, and TDRhelping define how the portfolio is measured, segmented, forecasted, and improved. Youll work closely with senior stakeholders across operations, DCs, PDAs, and post‑termination teams, using your advanced academic training to design predictive models, map lifecycle behaviour, and influence operational decisions. Whats in it for you? Youll architect an enterprise‑grade analytics framework (diagnostics modelling decisions reporting) and contribute directly to high‑impact outcomes, including: 1015% improvement in pre‑term & TDR collections 510% reduction in active DR drop‑off A rare opportunity for a brilliant quantitative graduate to move straight into a strategic analytics rolenot an internship, not a junior support position, but real portfolio ownership from day one. Key Responsibilities: Debt Review Lifecycle Diagnostics: Analyse active DR, pre‑term, and TDR behaviour including payment consistency, drop‑off risk, survival analysis, cure potential, and lifecycle value. Portfolio Segmentation & Mandate Performance: Build DC/PDA segmentation, cohort analyses, seasonal patterns, yield outlooks, and reinstatement forecasting. End‑to‑End Process Mapping: Map and analyse the full value chain (Acquisition DC PDA Collections Distribution) to identify bottlenecks and improvement opportunities. Predictive Modelling Suite: Design models related to drop‑off risk, reinstatement likelihood, settlement uplift, and workflow optimisation. Economic & Commercial Analysis: Assist in building a Termination Decision Framework (NPV, break‑even, ROI, scenario analysis). Performance Reporting: Develop daily/weekly/monthly reporting dashboards covering yield, ageing, reinstatements, and settlement lift. Job Experience and Skills Required: Education (minimum strict requirement ): Honours or Masters degree ONLY in: Statistics Data Science Mathematics Actuarial Science Economics Computer Science (Candidates without Honours/Masters cannot be considered.) Experience: No formal work experience required Must have demonstrated modelling ability through: Personal projects Academic research / dissertations Kaggle or other competitions Independent modelling work completed in your spare time Passion for data, modelling, and problem‑solving is essential Skills (technical): Strong SQL (academic or self‑taught) Python or R for modelling and statistical analysis Understanding of survival/propensity models, segmentation, regression methods Strong analytical, mathematical, and problem‑solving ability Exposure to BI tools (Power BI, Tableau, etc.) beneficial Ability to interpret financial metrics (NPV, ROI, profitability) Non‑negotiables (role‑critical): Must have Honours or Masters degree Strong communication skills with the ability to simplify complexity Curiosity and drive to convert analytics into practical execution Interest in credit analytics, collections optimisation, or financial behaviour Apply now! For more exciting Finance vacancies, please visit: