Graduate Actuary / Data Scientist

SUMMARY:
Are you a top-performing Honours or Master’s graduate who loves building models and solving complex analytical problems? This is your chance to own the analytics engine behind South Africa’s debt review performance—designing predictive models, mapping workflows, and driving measurable improvements across the full DR lifecycle.

POSITION INFO:
Join a specialist credit and collections environment where data is at the centre of strategy. In this role, you’ll build the single source of truth for active DR, pre‑Term, and TDR—helping define how the portfolio is measured, segmented, forecasted, and improved.

You’ll 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.

What’s in it for you? You’ll architect an enterprise‑grade analytics framework (diagnostics → modelling → decisions → reporting) and contribute directly to high‑impact outcomes, including:

• 10–15% improvement in pre‑term & TDR collections
• 5–10% reduction in active DR drop‑off

• 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.

• Education (minimum – strict requirement):
  
  • Honours or Master’s 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 Master’s 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