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Hi there πŸ‘‹ I'm Souvik Mondal

AI Product Manager Β· MBA, IIT Mandi (Data Science & AI)


Building products at the intersection of AI, data, and user insight. Currently driving AI go-to-market strategy at Webisdom while targeting AI Product Manager roles across India.


πŸš€ What I'm Currently Working On

  • πŸ€– AI Business Development & GTM strategy at Webisdom (TrainingLobe)
  • πŸ“¦ Uploading FCAT platform wireframes (React JSX) to GitHub
  • πŸ“– Deepening AI PM skills β€” LLMs, agentic AI, product strategy

🧠 About Me

  • πŸŽ“ MBA in Data Science & AI at IIT Mandi (2024–2026)
  • πŸ’Ό Ex-PM Ambassador at Flipr Innovation Labs β€” embedded PM on FCAT, a proctored career assessment platform serving 23+ colleges
  • πŸ”¬ Trained in mixed-methods research β€” SERVQUAL, thematic analysis, A/B test design, competitive teardowns
  • 🏭 Background in operations β€” Graduate Engineer at Linamar India
  • πŸ“ Based in Noida Β· Open to Pan-India relocation

πŸ› οΈ Skills & Tools

Product

PRD Roadmap A/B Testing ICE Kano

Data & Analytics

Python SQL Tableau Power BI Streamlit

Frontend & Wireframing

React JavaScript HTML5

Growth & SEO

Google Ads SEO Content Strategy


πŸ“Œ Featured Work

Project What I Did
FCAT Platform Β· Flipr User research, platform audit, 5 React wireframe systems, competitive analysis across 9 platforms, 4-phase roadmap
Myntra Bracket-Order Reduction Metric framework, Opportunity Solution Tree, PRD, A/B test design
JARVIS AI Masterclass Launch Β· Webisdom 6-week GTM campaign, SEO audit, bilingual content calendar
Inventory Dashboard Β· Unified Mentor Python/Streamlit dashboard, 46,000+ SQL transactions audited

πŸ† Achievements

  • πŸ₯ˆ 2nd Runner-Up β€” Himalayan Business Summit 2026
  • πŸ₯ˆ 1st Runner-Up β€” AiXcelerate 3.0 (2025)
  • ⚑ Participant β€” AiHack India 2025

πŸ“¬ Connect With Me

LinkedIn Email GitHub


Open to AI PM, Product Strategy, and Growth roles across India

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  1. credit-risk-default-prediction credit-risk-default-prediction Public

    End-to-end consumer credit default risk model using LightGBM ; feature engineering, target encoding with PSI drift checks, SHAP explainability, probability calibration, and decile-lift risk segment…

    Jupyter Notebook