Snapmint - Risk Analyst - Python/SQL

About Snapmint :

Indias booming consumer market has over 300 million credit-eligible consumers, yet only 35 million actively use credit cards. At Snapmint, were reimagining how credit workswith a product-first approach that puts the consumer experience at the center. Our EMI and Pay Later solutions are designed from the ground up to be intuitive, accessible, and frictionlessenabling millions of Indians to purchase what they need, when they need it, whether its fashion, electronics, or daily essentials.

From seamless onboarding to instant approvals and zero-cost EMIs, all our products are engineered to empower users while maintaining transparency and trust. We believe that enduring financial services are built not just on fair terms, but also on products that solve real problems with simplicity and scale.

Founded in 2017, Snapmint is now Indias leading online zero-cost EMI provider. With over 10 million consumers served across 2,500 citiesand doubling year on yearour growth is a direct outcome of building a world-class online product that people love and rely on.

About the Role :

The Risk Analytics owns the analytical foundation of the Risk portfolio, translating raw transaction and customer data into actionable insights that drive approval optimization, risk calibration, and customer profitability. This role sits at the intersection of risk management, product strategy, and data engineering, directly influencing credit decisioning, policy setting, and portfolio performance for a high-volume digital lending platform processing 1M+ daily transactions.

Unlike traditional credit risk analysts who focus on model building, this role emphasizes portfolio observability, cohort-based performance tracking, and real-time decisioning optimization across new and repeat user segments. You will own metrics that product, risk, and business teams depend on for decision-makingand you'll have the autonomy to challenge policy assumptions with data.

Core Competencies & Success Metrics :

Domain Expertise :

• Fintech : Familiarity with instant approval decisioning, high-velocity transaction flows, chargeback/fraud dynamics, and customer acquisition models.
• 1 to 3 years in credit risk analytics, or consumer fintech metrics (e.g., fraud, chargeback, risk).
• Credit & Risk Knowledge : Understanding of bureau scoring

Technical Skills :

• SQL Advanced : Write complex nested queries, window functions, and multi-stage aggregations. Optimize for performance on billion-row datasets.
• Python for Analytics : Pandas, NumPy, SciPy for ad-hoc cohort analysis, statistical tests (Chi-square, t-test, survival analysis), and simple predictive models (logistic regression).

Key Performance Indicators :

• Approval Optimization : Month-on-month approval rate improvement (target : +12% quarterly without degrading quality), funnel conversion lift from A/B tests.
• Insights Impact : # of policy recommendations adopted and their lift (e.g., "Tightened decision rule for 1st-time users, reduced 90+ DPD by 30 bps").

Working Days : Monday to Friday.