Pune, Maharashtra, India
Information Technology
Full-Time
KreditBee
Overview
Location : Bangalore
Experience : 3-4 years in Data Analytics (preferably in Fintech/NBFC Lending)
Role Summary
The Senior Data Analyst will play a pivotal role in shaping the LAP portfolio strategy by delivering data-driven insights across credit, collections, customer behavior, and channel performance. You will collaborate cross-functionally with Product, Credit, Risk, and Technology teams to optimize end-to-end lending operations.
Key Responsibilities
Business & Performance Analytics :
Experience : 3-4 years in Data Analytics (preferably in Fintech/NBFC Lending)
Role Summary
The Senior Data Analyst will play a pivotal role in shaping the LAP portfolio strategy by delivering data-driven insights across credit, collections, customer behavior, and channel performance. You will collaborate cross-functionally with Product, Credit, Risk, and Technology teams to optimize end-to-end lending operations.
Key Responsibilities
Business & Performance Analytics :
- Develop real-time dashboards and reports to monitor LAP disbursements, sourcing funnels, and collection efficiency.
- Provide deep-dive analysis on key metrics like yield, NPAs, bounce rates, TATs, and approval/rejection ratios.
- P&L analysis with actionable insights
- Work closely with the credit and risk teams to refine underwriting rules using data.
- Analyze borrower profiles to optimize approval rates and minimize delinquencies.
- Build early warning systems for identifying at-risk accounts and segments.
- Segment customers using demographic, financial, and behavioral data to drive better targeting and engagement.
- Analyze DSA and channel partner performance; optimize sourcing efficiency and partner payouts.
- Monitor cross-sell, top-up to identify growth opportunities.
- Evaluate pricing effectiveness using portfolio performance and competitor benchmarks.
- Analyze impact of product changes on conversion, risk, and profitability.
- Use funnel data to identify drop-offs and TAT issues in the digital LOS/LMS journey.
- Recommend workflow enhancements to improve user experience and reduce operational frictions.
- Build and maintain models for credit risk, prepayment, bounce prediction, etc., using machine learning or statistical techniques.
- Leverage alternate data sources (GST, bank statements, bureau data, property valuation) for deeper insights.
- Bachelor's/Master's degree in Statistics, Mathematics, Computer Science, Economics, or similar field
- 3-4 years of analytics experience in lending - ideally with a Fintech, NBFC, or Digital Lending platform
- Strong command of SQL and Python for data analysis and modeling
- Experience with BI tools like Power BI, Tableau
- Understanding of LAP-specific metrics (LTV, FOIR, property type impact, delinquency buckets, etc.)
- Exposure to LOS/LMS/lending systems
- Strong business acumen, with the ability to convert data into strategy
- Experience working in agile, cross-functional product and tech environments
- Experience with alternate underwriting data (e.g., GST, bank statement parsing, social data)
- Exposure to bureau data analytics (CIBIL, CRIF)
- Familiarity with property verification technology, or geolocation-based analysis
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