Kissht - Manager - Collections Analytics

- We are seeking a data-driven professional with deep expertise in collections analytics to drive strategy, performance monitoring, and modeling for our lending portfolio.

- The ideal candidate will combine strong analytical skills with practical experience in collections strategy, scorecard development, and cross-functional collaboration.

Key Responsibilities:

- Scorecard & Model Development: Design and enhance collection scorecards and early warning models to predict delinquencies and support proactive risk mitigation.

- Performance Analysis: Conduct vintage analysis, roll-rate and flow-rate tracking, and lag-based recovery modeling to understand portfolio dynamics.

- Segmentation & Strategy: Create advanced segmentation strategies (bucket-wise, geography-wise, and product-wise) to tailor collection approaches and optimize recovery.

- Strategy Experimentation: Collaborate with operations to run A/B tests and champion-challenger strategies across digital and field collections.

- KPI Tracking & Dashboards: Build and maintain dashboards to track key collection metrics such as DPD movement, cure rates, recovery curves, and agency productivity.

- Cross-functional Collaboration: Work closely with credit risk and policy teams to align collection strategies with risk appetite and loss expectations.

- Technology Enablement: Partner with data engineering and product teams to build real-time analytics for portfolio monitoring and collector performance insights.

Required Skills:

- Proficiency in SQL, Python, and Excel for data analysis, automation, and modeling.

- Hands-on experience in statistical modeling, including logistic regression and basic machine learning techniques for predictive analytics.

- Expertise in BI and visualization tools (Power BI, Tableau, Looker) for performance reporting and insights.

- Deep understanding of collections workflows, including dialer management, digital strategies, and agency/vendor performance tracking.

- Strong ability to translate data insights into actionable business recommendations and strategy enhancements.

Preferred Qualifications:

- 4-10 years of experience in collections or credit risk analytics in a consumer lending or fintech environment.

- Exposure to digital collections, tele-calling optimization, or field collections productivity models.

- Educational background in Statistics, Mathematics, Economics, Engineering, or a related quantitative discipline.