Product Leader · D2C & E-Commerce · AI/ML Enthusiast
PGDM – IIM Lucknow · B.Tech – NIT Jalandhar
"The best products sit at the intersection of customer obsession and technical curiosity."
I've spent 14 years building and scaling digital products — from omnichannel retail software at Capgemini to a 150M+ user D2C platform at vivo India. My edge is the rare combination of engineering roots, business school rigour, and a hands-on curiosity for emerging technology that refuses to stay purely strategic.
I believe PMs who understand the how build better products than those who only define the what. That belief is why I'm here.
| Domain | What I've shipped |
|---|---|
| D2C E-Commerce | End-to-end platform for vivo E-Store; OMS re-architecture cutting TAT by 30% |
| Conversion & Growth | Affordability Engine driving 40% uplift; multivariate A/B testing lifting leads 50% |
| AI / ML Integration | Google Vision AI for KYC automation; ML-based content ranking for travel bookings |
| Live Commerce | Gen Z-targeted live channel hitting 35% engagement rate |
| Marketplaces | Travel (Wandertrails), auto (CarDekho), professional services (Flatpebble) |
I've shipped AI features — KYC automation, recommendation engines, personalisation pipelines. But I found I was always one layer of abstraction away from asking the right questions of my data science teams.
So I went back to first principles. These repositories document that learning journey, mapped back to real product decisions:
- 📘 ML Specialisation Notes — Andrew Ng's curriculum, re-contextualised for product thinking: pricing models, churn prediction, demand forecasting
- 🧪 5-Day Gen AI Intensive — Google × Kaggle programme: prompt engineering, embeddings, multimodal AI
The goal is not to become a data scientist. The goal is to be the PM who can write the right brief, challenge the right assumptions, and evaluate model impact against real business metrics.
Building in public — connecting ML concepts to e-commerce product problems
🔨 E-commerce Funnel Analysis (in progress) Analysing cart abandonment, cohort retention, and conversion drop-offs using public retail datasets. Framed as a PM discovery exercise — what would I prioritise fixing, and why?
🔨 A/B Test Significance Calculator (in progress) A lightweight Python tool for experiment design — sample sizing, significance testing, recommended actions. Born from frustration at running underpowered tests early in my career.
🔨 Pricing Elasticity Model (in progress) Applying regression to model price sensitivity in consumer electronics — directly relevant to decisions I make at vivo.
Product & Strategy
Roadmapping OKRs P&L Management Agile/Scrum GTM Stakeholder Management
Data & Analytics
SQL BigQuery Google Analytics 4 Mixpanel Amplitude GTM
AI / ML
Python NumPy Pandas scikit-learn Computer Vision Recommendation Systems
Design & Delivery
Figma Adobe XD JIRA CRM
- ✅ Machine Learning Specialisation — Andrew Ng, Coursera (Supervised · Unsupervised · Advanced Algorithms)
- ✅ Certified Scrum Product Owner (CSPO)
- ✅ Design Thinking — IDEO
- ✅ 5-Day Generative AI Intensive — Google × Kaggle
I'm always interested in conversations about e-commerce product strategy, AI integration in consumer products, and building data-informed teams.
📍 Gurugram, India · Open to senior PM opportunities in AI-native and D2C product environments