Senior Collection Analytics & Modeling Executive

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About the Role:
We are looking for a data-driven professional to develop and optimize analytical models and collection strategies that improve debt recovery performance at SFinance.
This role combines predictive modeling, customer segmentation, collection strategy analytics, and performance monitoring to support data-driven decision-making, improve collection effectiveness, and optimize operational costs.
Key Responsibilities
1. Collection Modeling & Predictive Analytics
Develop and optimize predictive models to assess customers' payment behavior, recovery probability, and collection outcomes.
Build collection scoring models and predictive models for Promise-to-Pay (PTP), Roll Forward, Cure Probability, and Recovery Forecast.
Monitor model performance and recommend improvements based on actual collection results.
2. Collection Strategy & Customer Segmentation
Analyze customer behavior and repayment patterns across delinquency buckets.
Develop customer segmentation and recommend tailored collection strategies across call, SMS, digital, and field collection channels.
Conduct Champion-Challenger testing to evaluate and optimize collection strategies.
Identify opportunities to improve collection effectiveness and resource allocation through data-driven insights.
3. Data Analytics & Business Intelligence
Extract and analyze data from the Data Warehouse to support collection strategy development and operational decisions.
Develop dashboards and reports to monitor key performance indicators, including Collection Rate, Cure Rate, Roll Rate, Recovery Rate, RPC Rate, and PTP Fulfillment Rate.
Automate recurring reports and improve the efficiency of collection performance monitoring.
4. Model Monitoring & Optimization
Monitor model accuracy, stability, and effectiveness after implementation.
Perform model validation, recalibration, back-testing, and stress-testing where appropriate.
Identify model performance gaps and recommend corrective actions to maintain model reliability.
5. Cross-functional Collaboration
Work closely with Collection Operations, Risk Management, Data Engineering, IT, and Digital Transformation teams to implement analytical solutions.
Translate business requirements into analytical models and actionable recommendations.
Participate in AI/ML initiatives to enhance collection strategies and operational efficiency.