: Data Scientist About the Role

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 (Recent-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

Strong hands-on experience with Python & SQL

Experience with credit bureau data (CIBIL / Experian / Equifax)

📌 Data Scientist (Bengaluru)
🏢 Snapmint
📍 Bengaluru