Summary
Proxima Dasmohapatra is a Staff Machine Learning Engineer based in Berkeley with a decade of experience turning messy data into actionable products at scale. Currently leading ML efforts at Salesforce after progressing through data science and ML roles there and a brief data scientist stint at Apple, she blends randomized experiments, NLP, and recommender systems to drive customer adoption and retention. Her background spans production ML, data visualization, and ETL—skills honed earlier in analytics roles and during research at UC Berkeley extracting insights from “dark data.” She’s taught Python and guided graduate students, reflecting a knack for translating complex techniques into clear instruction and product-ready solutions. Known for combining rigorous experimentation with model interpretability (e.g., using LIME) she focuses on trust and measurability in ML-driven decisions.
10 years of coding experience
6 years of employment as a software developer
Master’s Degree, Information Management and Systems (Data Science & Analytics), Master’s Degree, Information Management and Systems (Data Science & Analytics) at UC Berkeley School of Information
Bachelor’s Degree, Information Technology, Bachelor’s Degree, Information Technology at College of Engineering and Technology, Bhubaneswar
Odia, English, Hindi, Spanish