Data Analyst - AM- Lending
- Salary
- ₹15–26 LPA
- Location
- Mumbai, India
- Experience
- Intermediate
About the company & role
About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm's mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the team: LRM Team Sales Operation team drives sales planning and execution through target setting, performance tracking, accurate reporting, data-driven insights, process management, and timely operational support to improve productivity and achieve business goals. About the role We are strengthening our Sales Planning and Distribution Strategy capability for Lending. As a Data Analyst, you will partner closely with the planning lead to turn business questions into clear analysis, models, and insights that drive sales planning, distribution design, and performance tracking. You will own day-to-day execution — data prep, analysis, dashboards, and scenario support — so leadership can make faster, better decisions. Key responsibilities -Support sales planning cycles (targets, capacity, territory/portfolio coverage, and resource allocation) with robust data and analysis -Build and maintain models for demand forecasting, productivity, channel/partner performance, and distribution effectiveness -Analyse sales funnel, conversion, and portfolio metrics to surface trends, gaps, and opportunities -Design and refresh dashboards / MIS for leadership reviews (weekly / monthly / quarterly) -Run scenario and what-if analyses for planning decisions (e.g., target stretch, channel mix, geographic prioritisation) -Partner with Sales, Credit, Operations, Finance, and Product to reconcile definitions, pull data, and validate insights -Ensure data quality, documentation, and consistent metric definitions across planning deliverables -Translate analytical findings into crisp recommendations and presentation-ready narratives for lea