Turning messy data into decisions that actually move numbers.
I build end-to-end data systems — from fraud detection pipelines to forecasting models — across fintech, e-commerce, and loyalty domains. I work at the intersection of analytics, ML, and business strategy.
Fraud detection obsessiveSQL query hoarder (2000+)Feature store architectNLP on messy survey dataA/B testing evangelistReward strategy redesignerRevenue leakage hunterPixel game developer, apparently
Bengaluru, KA, IND
Analytics principles
My multi-disciplinary
analytical process
First principles thinking
- ↳Breaking problems into their most basic form
- ↳Starting with the 'why' – down to the root cause
- ↳Building models using only fundamental truths
Exploratory Data Analysis
Feature Engineering
Data Storytelling
I'm a 360° Data Analyst
Here's my analytical work spanning across different critical business domains. Hover to get a peek. Detailed previews coming soon.
Fraud Detection
Rules & Anomalies
Growth & UI
Retention Analytics
Product Analytics
Checkout & A/B
Business Intel
Reporting Automation
A quick career summary
I've worked across industries — e-commerce, transportation, and fintech.
2025
2024
2023
2022
Data Analyst II
Poptech GrowthFeb 2024 – Present- •Built a behavioral UPI fraud detection system using transaction velocity, payee diversity, error-code patterns, and amount clustering — reduced fraud-related losses by 95%
- •Applied NLP on NPS survey data to surface customer pain points; findings directly drove Tier-3 brand delisting and Tier-1 onboarding, plus a weighted SLA model that improved brand processing SLA by 12%
- •Engineered a customer feature store with 100+ behavioral and transactional features across UPI, e-commerce, credit card, and loyalty datasets — supporting ML pipelines and cutting query costs via optimized data modeling
- •Built a Contribution Margin forecasting model integrating pricing, coin burn, logistics, and partner costs — reduced financial reporting lag by 1.5 months and enabled proactive unit-economics decisions
- •Redesigned reward issuance strategy from blanket to revenue-linked allocation — reduced issuance by 84% MoM while maintaining the same redemption cost
- •Partnered across business, product, backend, and data engineering to audit pipelines, surface data flaws, and flag unreported revenue leakage
Data Analyst I
Poptech GrowthJun 2023 – Feb 2024- •Owned full-funnel attribution and cohort analysis for the Razorpay × POP checkout integration — reduced CAC from ₹40 to ₹10
- •Led credit card funnel analytics: diagnosed drop-offs, resolved data source vs. reporting lags, ran CIBIL-reject maturity scrubs for retargeting
- •Built a centralized SQL repository of 2000+ reusable queries and 40+ automated dashboards — migrated company to Metabase, cutting infra costs by 30% and enabling self-serve KPI tracking
- •Ran A/B tests on D2C website floater designs — drove a 20% increase in signup conversion rate
Data Analyst Intern
RapidoJun 2023 – Nov 2023- •Optimized SQL pipelines and built dashboards for the Bike Lite experiment
- •Conducted RCA on RPR, RPH, and retention metrics across Bangalore and Hyderabad — generated insights that improved city-level operational strategy
Toolkit & Methods
Languages & Querying
PythonSQLPySpark
Platforms & Data Infra
DatabricksELT PipelinesMaterialized ViewsQuery Optimization
Visualization & BI
TableauPower BIMetabaseExcelGoogle Sheets
Analytics Methods
A/B TestingFunnel & Cohort AnalysisNLPAnomaly DetectionFraud ModelingRCAEDAFeature Engineering
Case Studies & Projects
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