kreditbee - Senior Data Analyst - Loan Origination System

Location :

Experience :

Role Summary

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
  

Risk & Credit 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.
  

Customer & Channel Analytics

• 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.
  

Product & Pricing Strategy

• Evaluate pricing effectiveness using portfolio performance and competitor benchmarks.
• Analyze impact of product changes on conversion, risk, and profitability.
  

Process & Funnel Optimization

• 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.
  

Advanced Analytics & Modeling

• 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.
  

Required Skills & Qualifications

• 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
  

Good To Have

• 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