Data Analyst - Customer Experience

About Snapmint:

Snapmint is a leading fintech company redefining access to consumer credit in India. With over 10 million customers across 2,200+ cities, our zero-cost EMI platform enables responsible purchases without the need for a credit card across categories like fashion, electronics, and lifestyle. India has over 300 million credit-eligible consumers, yet fewer than 35 million actively use credit cards. Snapmint addresses this gap by offering a trusted, transparent alternative grounded in financial inclusion and ethical lending practices.

Founded in 2017, Snapmint is a profitable, high-growth company doubling year-on-year. Our founding team, alumni of IIT Bombay and ISB, brings deep experience from companies like Oyo, Ola, Maruti Suzuki, and has successfully built and exited ventures in ad-tech, patent analytics, and bank-tech. We are building the future of responsible consumer finance, simple, transparent, and customer-first.

Key Responsibilities:

• Own end-to-end analytics using SQL and Python affecting customer experience (CX), communications, loan repayments, product journeys affecting customer experience and seller experience
• Translate raw, complex datasets into clear insights, narratives, and actionable recommendations for Product, Operations, and CX teams.
• Partner with product and collections team to redesign repayment flows, customer experience flows and support in improving collection efficiencies by optimizing communication across various channels
• Drive root cause analysis for various incidences and suggest corrective and preventive actions to avoid such incidents in the future.
• Measure effectiveness of proactive communications (SMS, WhatsApp, Email, IVR)
• Run pre/post and A/B analysis on Message content, channel selection, timing and frequency
• Identify communication gaps that result in customer confusion, complaints, or repeat calls.

Technical Skills :

SQL (Advanced)

• Write complex, optimized SQL queries including nested queries, CTEs, window functions, and multi-stage aggregations.
• Perform cohort, funnel, and trend analysis on billion-row datasets, optimizing performance.

Python for Analytics

• Use Python (Pandas, NumPy) for exploratory analysis, feature creation, and deep dives.
• Automate recurring analytical workflows and reporting pipelines.

Educational Qualifications: Bachelor's degree in mathematics, engineering, statistics or related fields