We are hiring a Data Scientist to own end-to-end credit underwriting models for a high-scale fintech product. This role spans model development, real-time deployment, monitoring, and continuous improvement, directly impacting approval rates, fraud, credit losses, and GMV.
What You’ll Do
Credit Underwriting & Modeling
- Build and maintain credit risk models using Logistic Regression, XGBoost / LightGBM and deep learning
- Design underwriting strategies for NTC (New-to-Credit) users using alternative & behavioural data
- Balance credit risk, fraud risk, and conversion in checkout flows
- Design real-time features with strict latency SLAs (<100 ms):
- Velocity & frequency features
- Rolling window aggregates
- Behavioural & transactional signals
- Implement incremental / online feature updates (mean, std, EWMA, decay)
- Ensure training–serving feature parity using feature stores or custom pipelines
- Partner with Risk teams to define:
- Score cut-offs, bands, and guardrails
- Policy rules layered over ML models
Experimentation & Business Impact:
- Measure impact on:
- Approval rate
- FPD & delinquency
- Portfolio loss & margins
What We’re Looking For:
- 1-3 years experience in Credit Risk / Lending / Cards
- Solid hands-on experience with Python & SQL
- Experience with credit bureau data (CIBIL / Experian / Equifax)
📌 Data Scientist (Bengaluru)
🏢 Snapmint
📍 Bengaluru
Reply to this offer
Impress this employer describing Your skills and abilities, fill out the form below and leave Your personal touch in the presentation letter.