Anirban Ghosh

Product Manager

Noida, Uttar Pradesh, India4 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

National Finalist in HUL Techtonic Season 1.
Led significant data automation projects at IndiaMART.
Achieved 90% accuracy in sales predictability model.

Stackforce AI infers this person is a Data Analytics and Product Management professional in the SaaS industry.

Contact

Skills

Core Skills

Product ManagementData Analytics

Other Skills

API OptimizationApache PigBusiness IntelligenceCascading Style Sheets (CSS)Customer Journey MappingData AnalysisData AutomationData MiningData Warehouse OptimizationDatabase ManagementDebuggingFigma (Software)GSTGST MatchmakingHBase

About

National Finalist and Campus Winner of HUL Techtonic Season 1. Campus Finalist for Reliance T.U.P. 5.0. All India 4th in Smart India Hackathon 2018. Interested in Data Analytics, Product Management and IT Consulting. Worked in the following domains - Big Data Analytics using Hadoop Distributed File System, Machine Learning, backend development in Python Flask.

Experience

Indiamart intermesh limited

2 roles

Product Manager

Promoted

Jan 2025 – Present · 1 yr 2 mos

Assistant Product Manager

Jun 2022 – Jan 2025 · 2 yrs 7 mos

New Sales Division, WEBERP, GST Matchmaking – Business Intelligence
 Optimized and modified data warehouse engine for targeting free sellers with accurate Buylead alert emails,
notifications and WhatsApp communication - 100 new customer addition per week (~10% of weekly sale no. of NSD)
 Led the project of migrating 170 Weberp pages and 40 schedulers to Centralized Email System, by working in close
collaboration with 15+ teams and 40 members (with Netcore Integration | 20X improvement in Vendor api response)
 Facilitated the addition of 75L active GSTs (~60% of total base) in master database in last 2 fiscal years
 Automated the weekly data assignment process (~70L free sellers) to 3000+ sales teams in data warehouse, with
improved disposition logics and focused filters, resulting in 1.5Cr+ revenue in FY 23-24
 Improved accuracy of GST Matchmaking algorithms (both real time and for Hot Lead Generation machine) by 40% -
auto approval success% reached all time high of 21%
 Designed the WhatsApp journey and set up cron logic for capturing intent of newly added customers towards
accounting software subscriptions of sibling companies - ~70% onboarding ratio since launch in Feb’24
 Worked on Sale Predictability POC model by using KNN Clustering and Gradient Boosting Classifier to provide data
segmentation for sales executive on sale probability, with >90% accuracy
 Optimized GST APIs P95 response to less than 20ms, and enabled multiple read and write APIs for different teams and
GST update screens across IndiaMart, also provided architectural wireframe for GST OTP verification journey launch
 Identified a key bug in seller tracking journey across IndiaMart server logs (seller desktop, mobile site and trade), and
increased traffic of unique sellers by 40% in Kibana