Summary
Naishadh Parmar is a data-driven risk analyst with 8 years of experience applying statistical modeling, ML, and production analytics to prevent fraud and optimize business outcomes. Currently at eBay, he’s credited with averting an estimated ~$430M in potential losses, building XGBoost classifiers for freight-forwarder detection, and running A/B tests that unlocked $3.3M in incremental GMV. He combines hands-on engineering (Python, SQL, Spark, Databricks, Azure) with product-minded experimentation and clear stakeholder storytelling using Tableau and Kibana. A Columbia MS in Data Science graduate, he has built end-to-end pipelines, transfer-learning computer vision models for historical maps, and LLM-based annotation tools—demonstrating comfort across classical stats, deep learning, and modern LLM workflows. Notably, he translates ambiguous business problems into operational risk controls and metrics that scale across teams.
9 years of coding experience
2 years of employment as a software developer
Indian Institute of Technology Kanpur
Ryan International School
Master of Science - MS, Data Science, Master of Science - MS, Data Science at Columbia University
English, Hindi, German, French, Gujarati