Abhay Pawar
Machine Learning Engineer at Snap Inc.
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolAbhay Pawar is a Machine Learning Engineer with a decade of experience building large-scale predictive and recommendation systems across e-commerce, retail, and financial services. Currently at Snap after roles at Pandion, Stitch Fix, and Instacart, he has driven inventory prediction, replacement recommendations, product taxonomy, and search-ranking improvements that materially boosted service quality. He combines an MS in Data Science from Columbia with early career work in credit risk and uplift modeling, producing business-impacting models used for campaign targeting and risk mitigation. A hands-on engineer, he contributes to tooling for feature exploration and visualization (notably a univariate plotter with trend-change analysis), reflecting a strong focus on interpretable feature engineering. Collected experience in both research settings (water-level change analysis) and production ML gives him a rare blend of domain breadth and production rigor.
10 years of coding experience
8 years of employment as a software developer
Indian Institute of Technology MadrasMaster’s Degree MS in Data Science, Master’s Degree MS in Data Science at Columbia University
English, Hindi, Marathi
Github Skills (8)
data-visualizations10
pandas10
data-visualization10
data-visualisation10
feature-engineering10
python10
matplotlib10
machine-learning9
Programming languages (1)
Github contributions (5)
abhayspawar/featexp
Sep 2018 - Jul 2020
Feature exploration for supervised learning
Role in this project:
Data Scientist
Data ScientistContributions:2 releases, 2 reviews, 95 commits in 1 year 10 months
Contributions summary:Abhay contributed significantly to the `featexp` repository, which focuses on feature exploration for supervised learning. Their primary contribution was implementing a univariate plotter, a tool for visualizing the relationship between individual features and the target variable. They added functionalities to the plots, including trend change analysis and trend correlation calculations, demonstrating a focus on data analysis and visualization within the context of feature engineering.
pytorchsupervised-learningsuperviseddeep-learningmachine-learning
abhayspawar/Machine-Learning-course-assignments
Sep 2017 - Jul 2019
Contributions:2 commits, 2 pushes, 1 branch in 1 year 10 months
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