---
title: "Souradeep Chakraborty - Product in India | Tal"
description: "Meet Souradeep Chakraborty, Product @ Scapia | ex-Flipkart, Morgan Stanley based in India."
image: "https://tal.club/meet/s-c/share-image"
---

# Souradeep Chakraborty on Tal

## Headline

Product @ Scapia \| ex\-Flipkart, Morgan Stanley

## About

Hey\! I'm Souradeep \(Saura\)\. Currently building at Scapia \- a fintech aiming to revolutionise how young India thinks about and does travel\. Previously led several charters within Flipkart at FCC \- https://www\.flipkartcommercecloud\.com/ as an IC PM with \~4 yrs experience across domains like fintech, ecommerce & SaaS \(joined directly after undergrad as part of the prestigious APM program\)\. During my undergrad, I got exposure to a variety of technical opportunities in fields like data science, machine learning, electronics and mathematical finance that helped nurture and develop a knack for data\-driven problem\-solving\. Coupled with an innate instinct for user centricity and skill in innovative problem solving, I wholeheartedly love my work currently, where I can create deep lasting impact across the Product lifecycle \(with special expertise in building 0\-1 products\)\. I also love philosophy, music and academic/industrial research; having previously delved into deep/reinforcement learning and published a few papers on the applications of these technologies to 5G communications as well as finance\.

## Location

India

## Work experience

Product at Scapia, Aug 2025 \- Present · 1 yr 1 mo, Bangalore Urban, Karnataka, India, Shaping the future of travel with relentless product innovation at the intersection of fintech and wanderlust

Product Manager at Flipkart, Jun 2021 \- Aug 2025 · 4 yrs 3 mos, Search & Browse, Catalog, Pricing

Quantitative Risk Analyst at Morgan Stanley, Jan 2021 \- Jun 2021 · 6 mos, Mumbai, Maharashtra, India, \- Developed a new optimised model for Corporate Credit risk that is able to tackle statistical outliers observed during Mar\-Apr 2020 of the COVID\-19 pandemic, thereby reducing residual errors by over 15%\. \- Automated the process of generating systematic loan data using python by containerizing codes from kdb\+/Q, R, and STATA, reducing execution time drastically from 30 mins to <1 min per week\. \- Performed investigative research into the core components of Morgan Stanley’s vast corporate credit portfolio and analyze the top drivers of risk as well as nuances like multicollinearity of regressors\. Received a PPO\.

Machine Learning Engineer at RAFA AI, May 2020 \- Jan 2021 · 9 mos, Sunnyvale, California, United States, \- Primarily responsible for developing multiple key features and releases including the flagship Ramanujan AI model \(using deep language models\) for multi\-horizon timeseries forecasting \(generating weekly forecasts\)\. \- Created workbenches for managing 40\+ years of financial data, thereby saving over 30% \(or 5 seconds\), in execution time for low\-latency services\. \- Saved over $8/hr in computational costs using data parallelism with multiple GPUs fortraining large models\.

Computational Finance Intern \- Fixed Income Division at National Stock Exchange of India Limited, Apr 2020 \- Jul 2020 · 4 mos, \- Developed a fixed\-income attribution model, able to account for 100% complex factors to decompose portfolio returns\. \- Stress\-testing using Python on over 300 fixed\-income portfolios offered by Indian banks \(like the SBI Corporate Bond Fund\), under varying market conditions\.

## Education

Undergraduate, Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani \- Goa Campus

CBSE, Science class 12, DPS Ruby Park, Kolkata

[View the original profile](https://tal.club/meet/s-c)

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