Upender Phogat

Upender Phogat is an experienced Data Scientist at Gartner, specializing in developing automated systems and recommendation engines. Since March 2020, Upender has led initiatives such as an automated post-call follow-up email system, achieving an 85% recall rate, and a recommendation engine that accurately predicts client interests with a 67% hit rate. Upender’s expertise encompasses prompt engineering, vector databases, and advanced machine learning techniques, utilizing tools such as Streamlit, LLMs, and XGB Ranker. Prior to Gartner, Upender worked as an Associate Data Scientist at Innoplexus, focusing on data crawling, classification, and actionable insights from diverse digital sources, with a foundational background in data analysis and web scraping. Upender holds a Bachelor of Technology degree from the Indian Institute of Technology (Banaras Hindu University).