Devjit Chakravarti

Background

About Devjit Chakravarti

As a seasoned Staff Machine Learning Engineer with a rich history spanning over a decade in data science, machine learning, and product management, I've dedicated my career to leveraging advanced analytics and machine learning technologies to drive innovation and efficiency across various industries. Currently, at KoBold Metals, I'm at the forefront of developing ML-enabled tools and products aimed at revolutionizing the exploration of critical battery minerals, contributing to the global effort to combat climate change. My journey through high-impact roles at DoorDash, Lyft, Facebook, and YouTube (Google) has equipped me with a unique blend of skills in machine learning, data science, product analytics, and strategic research. I've led teams in developing and deploying cutting-edge ML models, creating robust data architectures, and driving product analytics that inform growth strategies and operational improvements. At DoorDash, I pioneered a novel deep learning approach to food prep prediction. My tenure at Lyft was marked by leading the development of telematics-based risk signals, improving travel time and traffic estimation through advanced machine learning models. I hold an MS in Aerospace Engineering from Stanford University and a BS from the Massachusetts Institute of Technology, underscoring my strong analytical foundation and problem-solving capabilities. I am passionate about using advanced ML to solve complex problems. My goal is to continue innovating within the realm of machine learning and analytics, pushing the boundaries of what's possible. I'm always open to connecting with like-minded professionals and exploring opportunities where my expertise can contribute to meaningful advancements.