Natalie Epstein
Doctoral Student
Doctoral Student
Natalie Epstein is a PhD Candidate in Technology and Operations Management at Harvard Business School. She received her B.S. in Industrial Engineering and M.S. in Operations Management from Universidad de Chile. Prior to Harvard, Natalie worked as a Business Analyst at McKinsey & Company and as a Research Associate at Universidad de Chile. Her research interests are in empirical operations in retail, e-commerce, logistics, and consumer behavior.
Natalie Epstein is a PhD Candidate in Technology and Operations Management at Harvard Business School. She received her B.S. in Industrial Engineering and M.S. in Operations Management from Universidad de Chile. Prior to Harvard, Natalie worked as a Business Analyst at McKinsey & Company and as a Research Associate at Universidad de Chile. Her research interests are in empirical operations in retail, e-commerce, logistics, and consumer behavior.
- Cases and Teaching Materials
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- Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021. View Details
- Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021. View Details
- Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.) View Details
- Area of Study