Apr 2024 – May 2025 · 1 yr 1 mo · Gurugram, Haryana, India · On-site

• Product Development:
• Developed the Merchant Cash Advance (MCA) whitelisting base from scratch, compiling a portfolio of approximately 1.3L merchants. This led to a 10X increase in GMV and a 7X rise in transaction volume of merchants, supporting the broader goal of building a trusted merchant base that views Mobikwik as their present and future financial partner. (SQL + Excel)
• Data Analysis and Reporting:
• Build an end-to-end Datamart from the ground up to capture and analyze user behavior across 450+ data points, enabling optimized policy changes, limit adjustments, and loan offerings for ZIP and MCA users. (SQL + Excel)
• MOM Risk Cohorts: Developed 15+, 30+ and 90+ risk cohorts to monitor month-over-month (MOM) risk metrics at both the user and principal outstanding (POS) levels. (SQL + Tableau)

Jan 2023 – Mar 2024 · 1 yr 2 mos · Gurugram, Haryana, India · On-site

• Data Analysis and Reporting:
• Automated MCA collection monitoring through a real-time dashboard: This provides insights into unpaid rates by bucket (1-30 days, 31-60 days, etc.) and enables data-driven decision-making to reduce default rates and achieving resolution rates of 70% for 1-30 days bucket and 25% for 31-60 days bucket. (SQL + Metabase)
• Created dynamic WOW Funnel reports (tracking MCA product growth and risk metrics) and ZIP Merchant Analysis reports using advanced data visualization tools, contributing to a 30% reduction in ZIP delinquency. (SQL + Excel + Tableau).
• Team Management & Collaboration:
• Partnered with cross-functional teams (Product, Tech, Analytics) and key stakeholders (VPs, Directors) to implement and uphold effective risk management practices.
• Trained new hires in MCA underwriting, providing mentorship to help them efficiently manage up to 20 cases per hour.

Jun 2022 – Jan 2023 · 7 mos · Gurugram, Haryana, India · On-site

• Revenue Growth & Digital Marketing Analytics:
• Designed city-level performance trackers to evaluate their contribution to overall revenue, measuring key metrics such as unique SKUs, dump, GMV, total carts, AOV, and ASP. This led to an increase in unique SKUs from 18 to 32 and a reduction in dump from 10L to 2L per day. (SQL + Excel)
• Created UX funnel visibility for paid marketing channels to track key metrics, including Play Store funnel, installs, CPI, CAC and conversion rates. (SQL + Excel)
• Conducted multiple experiments with varying delivery charges to assess their impact on revenue and retention. (SQL)

Nov 2020 – Jun 2022 · 1 yr 7 mos · Noida, Uttar Pradesh, India · On-site

• Data Analytics & Data Engineering:
• Build performance metrics dashboards for U.S.-based pharmacy stores, tracking KPIs (Key Performance Indicators) such as average daily sales, average order value, average prescriptions filled per day, and inventory metrics. (SQL + Tableau)
• RFM analysis: Conducted RFM analysis (Recency, Frequency, Monetary) to identify the most valuable potential customers for targeted campaigns, aimed at improving response rates, sales, and profitability. (SQL)
• Worked on ETL layers: Ingestion, Curation and Serve (Used Spark/Scala/Structured Stream/Batch Job on Databricks).

Jun 2019 – Jul 2019 · 1 mo · Gurugram, Haryana, India · On-site

• Multi Touch Attribution - Logistic Regression Model:
• Implemented a multi-touch attribution model using logistic regression to allocate a monthly marketing budget of 4 crores across various digital channels, resulting in an 18% improvement in marketing ROI. (SQL + Python)