Youll join a specialist credit and collections business where data drives strategy and execution. The organisation operates at the intersection of regulation, analytics, and collections, partnering closely with Debt Counsellors (DCs), Payment Distribution Agencies (PDAs), and recovery teams to optimise outcomes across the full debt review lifecycle. This is an environment that values innovation, accountability, and commercially driven insight. Key Responsibilities: Analyse Active DR, Pre-Term, and TDR portfolios to model payer behaviour, payment consistency, drop-off risk, cure potential, and lifecycle value Build and own portfolio segmentation, DC/PDA performance views, cohort analysis, seasonal trends, KPIs, yield forecasts, and reinstatement metrics Map end-to-end debt review workflows (Acquisition DC PDA Collections Distribution) and identify optimisation opportunities Design and maintain a predictive modelling suite to support operational and commercial decisions Develop a Termination Decision Framework using NPV, break-even, ROI, and sensitivity analysis Establish daily, weekly, and monthly BI reporting and mandate-level dashboards covering yield, ageing, reinstatements, and settlement uplift Partner with operational and senior stakeholders to translate analytics into execution-ready playbooks Job Experience and Skills Required: Education: Bachelors degree in Statistics, Data Science, Mathematics, Actuarial Science, Economics, or Computer Science Honours or Masters degree advantageous Experience: Minimum of 5 years experience in credit or collections analytics, preferably within debt review or regulated environments Proven delivery of predictive models and operational optimisation initiatives Demonstrated ability to convert analytical insight into measurable financial and operational outcomes Skills Advanced SQL Python or R for modelling and statistical techniques (segmentation, survival analysis, propensity modelling) Strong financial modelling capability (NPV, profitability, amortisation, ROI, sensitivity analysis) BI reporting and dashboard development across daily, weekly, and monthly cadences End-to-end process mapping and workflow optimisation across DCs, PDAs, and post-termination recovery Non-Negotiables: Strong understanding of the National Credit Act (NCA), debt review processes, PDAs, and DC behaviour Ability to influence operations and senior stakeholders with clear, confident communication Proven ability to turn analytics into execution through practical guardrails, playbooks, and measurable performance lift For more exciting Actuarial and Analytics vacancies, please visit:

Join a specialist credit and collections environment where data drives strategy. Youll architect the end-to-end debt review performance universe, design a predictive model suite, and partner with operations to optimise workflows across DCs, PDAs, and post-termination recovery. Why work here? High-impact seat at the table: Youll define how the portfolio is measured, segmented, forecasted, and improvedfrom drop-off prevention to settlement lift. Expect deep collaboration with senior stakeholders, a clear mandate to challenge and improve processes, and the satisfaction of seeing your models directly lift collections. Whats in it for you? Build an enterprise-grade framework (diagnostics modelling commercial decisions reporting) and hit bold year‑1 outcomes: 1015% lift in pre‑term & TDR collections and 510% reduction in active DR drop‑off. Key Responsibilities: Debt Review Lifecycle Diagnostics: Analyse active DR, pre‑term, and TDR to model payer behaviour, payment consistency, drop‑off risk (e.g., survival analysis), cure potential, and lifecycle value. Portfolio Segmentation & Mandate Performance: Create DC/PDA performance views, seasonal patterns, cohort tracking, and segment‑specific KPIs, yield outlooks, and reinstatement trends. End‑to‑End Process Mapping & Workflow Optimisation: Map current state (Acquisition DC PDA Collections Distribution) including systems alignment. Predictive Modelling Suite. Economic & Commercial Analysis: Build a Termination Decision Framework (NPV, break‑even, ROI, sensitivity analysis) and deliver a scorecard for termination timing and strategy. Performance Measurement & Reporting: Stand up daily/weekly/monthly BI reporting and mandate‑level dashboards covering yield, ageing, reinstatements, and settlement lift. Job Experience and Skills Required: Education (minimum): Bachelors degree in Statistics, Data Science, Mathematics, Actuarial Science, Economics, or Computer Science (Honours/Masters beneficial). Experience: 5 years in credit/collections analytics or debt review performance analysis. Proven delivery of predictive models and operational optimisation in a regulated environment. Experience translating analytics into operational playbooks and measurable financial outcomes. Skills (technical): Advanced SQL ; Python/R for modelling; and statistical methods (segmentation, survival/propensity modelling). Financial modelling ( NPV, profitability, amortisation, ROI, and sensitivity analysis ). BI reporting (daily/weekly/monthly cadence) and dashboarding. Workflow and process optimisation across DCs, PDAs, and post‑termination processes. Non‑negotiables (role‑critical): Strong understanding of NCA , debt review processes, PDAs, and DC behaviour. Ability to influence operations and senior stakeholders with clear, no‑surprises communication. Demonstrated capability to convert analytics into execution (guardrails, playbooks, and measurable lift). Apply now! For more exciting Finance vacancies, please visit: