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Vibhati Burman

@vibhatiburman

Machine Learning Engineer at PayPal who developed models that lifted eligibility by 45% and increased funded loans.

At PayPal, I developed a Transformer-based embedding model to identify Small Business Owners in the consumer population, achieving a 45% lift in eligibility. I also developed a CatBoost model for credit marketing that improved KS by 8 points and increased funded loans in the >$25K segment from 3 to 180.

At Flipkart, I built a CatBoost classification model to identify returns eligible for technician-check bypass, reducing operational costs and improving RNPS by 700 bps. I also developed an attention-based NLP model that improved geocoding accuracy by 3%.

At TCS Innovation Labs, I developed pricing and forecasting solutions for retail. My markdown pricing solution increased a retailer’s margin by 8%, while a demand forecasting and assortment solution contributed to a 41% revenue hike.

I also worked on a reinforcement-learning proof of concept for dynamic pricing of perishable items, with simulations indicating a 7–11% rise in net revenue. My work includes publications on retail pricing, demand forecasting, and geospatial data.

Experience

Work history, roles, and key accomplishments

PA

MTS1- Machine Learning Engineer

Jun 2024 - Sep 2026 (2 years 3 months)

Developed a Transformer-based embedding model for Small Business Owner identification, achieving 3.8x higher response rate and 2x conversion rate. Built CatBoost models for credit marketing and risk, improving KS by 8-10 points and driving funded loans from $3M to $14.2M.

Python SQL Transformers CatBoost Machine Learning Credit Marketing Risk Modeling

FL

Data Scientist

Flipkart

Jan 2022 - Jun 2024 (2 years 5 months)

Built a CatBoost classification model to identify high-confidence returns for technician-check bypass, reducing operational costs and improving RNPS by 700 bps. Developed an attention-based NLP model for address geocoding, improving accuracy by 3%.

Python SQL CatBoost NLP Attention Mechanisms geocoding

TL

Researcher

TCS Innovation Labs

Aug 2017 - Jan 2022 (4 years 5 months)

Developed markdown pricing solutions using KNN, boosting, and ANN, increasing retailer margin by 8%. Created demand forecasting and assortment optimization models with XGBoost and ANN, boosting revenue by 41%. Built a dynamic pricing proof of concept using reinforcement learning, showing 7-11% net revenue rise.

Python PySpark KNN XGBoost ANN Reinforcement Learning Q Learning SARSA DQN LSTM Demand Forecasting Recommendation Systems

Education

Degrees, certifications, and relevant coursework

IK

Indian Institute of Technology, Kharagpur

M.Tech, Multimedia Information Processing

Grade: 8.7/10

Pursued M.Tech in Multimedia Information Processing with a grade of 8.7/10.

BD

Bhilai Institute of Technology, Durg

B.Tech, Electronics and Telecommunication Engineering

Grade: 8.8/10

Pursued B.Tech in Electronics and Telecommunication Engineering with a grade of 8.8/10.

Tech stack

Software and tools used professionally

PySpark

Python

SQL

XGBoost

CatBoost

Seaborn

Matplotlib

Availability

Looking for a job

Location

India

Authorized to work in

Salary expectations

8309k+ INR

Job categories

Machine Learning Engineer Data Scientist

Skills

Machine Learning predictive modeling Deep Learning Reinforcement Learning Natural Language Processing Demand Forecasting Dynamic Pricing Recommendation Systems geocoding Classification CatBoost Transformer Models XGBoost Artificial Neural Networks K Nearest Neighbors

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