Headline

Data Analyst @ Paytm | SQL | Python | Power BI | Advanced Excel | Data Visualization | Data Cleaning | Pandas | Statistical Analysis | Data Modeling |

About

I don't just analyze data — I turn it into decisions that move businesses forward. From engineering automated pipelines that eliminated 3–4 day reporting lags, to building ML models that hit 0.87 ROC-AUC, I've spent my career making sure every dataset I touch delivers measurable impact — not just pretty charts. What I've delivered so far: 🔹 Built an end-to-end analytics pipeline processing 20,000+ bot sessions/month for Paytm's fintech lending product — cutting manual reporting effort by 70% 🔹 Identified 8 merchant friction clusters that directly shaped 3 backend sprint priorities and contributed to an estimated 18% improvement in deflection rate 🔹 Engineered 10+ predictive features from Tesla stock data and delivered an XGBoost model with 0.87 ROC-AUC — selected as the production classifier 🔹 Analyzed 145,000+ records across 50+ countries to uncover global AI adoption trends — surfacing Agriculture as the #1 adopting sector and the 55+ demographic as the fastest-growing segment

Location

Greater Bengaluru Area

AI stack

hugging face

notion

openai

replit

Work experience

Data Analyst at Paytm, Feb 2026 - Present · 5 mos, Bengaluru, Karnataka, India, ▸ Engineered an automated monthly analytics pipeline processing 20,000+ bot sessions across IVR and chat channels, reducing manual reporting effort by ~70% and enabling real-time product monitoring for the fintech lending vertical. ▸ Built a multi-label issue clustering system that categorized merchant conversations into 8 distinct friction clusters (NOC delays, payment failures, EMI bugs, feature gaps), tagging each with handover rate and CSAT sentiment — directly informing 3 backend sprint priorities. ▸ Developed repeat-merchant detection logic to surface chronic unresolved issues by flagging merchants with 3+ escalated sessions within the same day, reducing escalation backlog by identifying the top 12% of high-friction users. ▸ Delivered structured product recommendations with effort estimates and deflection rate projections to Engineering, Backend, and KB teams; insights consumed by P4B Lending leadership to prioritize a roadmap with an estimated 18% deflection rate improvement.

Data Analyst at Snapcast Solution, Jan 2025 - Jun 2025 · 6 mos, Greater Bengaluru Area

Education

Master of Computer Applications - MCA, Computer Science, Garden City University

Master of Science, Garden City University