About

Arash Pourhabib is a Senior Data Scientist at Google with expertise in forecasting, experimental design, and machine learning. With over 8 years of relevant experience, he has a proven track record of developing algorithms for statistical calibration of computer models, large-scale stochastic optimization, and imbalanced classification. Before joining Google, Arash worked as a Staff Data Scientist at Walmart where he developed forecasting algorithms for item demand at Walmart.com and Walmart Stores. He also worked as an Assistant Professor of Industrial Engineering and Management at Oklahoma State University where he taught courses related to design of experiments, quality control, and Python programming. Arash holds a Doctor of Philosophy (PhD) in Industrial Engineering from Texas A&M University, where he developed algorithms for statistical calibration of computer models. He also has a Bachelor's degree in Industrial Engineering from Sharif University of Technology. Arash's technical expertise includes Data Science, Research Science, Machine Learning, and Python. He is a highly analytical and detail-oriented professional who is passionate about using data to solve complex business problems. With his strong background in statistical modeling and machine learning, Arash is able to develop data-driven solutions that drive business growth and improve operational efficiency. Overall, Arash is a talented Senior Data Scientist with a wealth of experience in developing algorithms for statistical modeling and machine learning. His expertise in forecasting, experimental design, and machine learning make him a valuable asset to any organization looking to leverage data to drive business growth.