Rachel Warren Headshot

Rachel Warren

Alumni (MIMS 2021)


Data science, tech policy, algorithmic fairness, misinformation


Data Science
Information Policy
Software Development



Rachel entered the School of Information's masters program hoping to reorient her technical skills towards reducing inequality. Her three main areas of interest are algorithmic fairness and ethics, data science and computational tools to combat misinformation and poverty, and the implications of data in the criminal justice system. She is a 2020 CTSP fellow, and her project focuses on building tools to help public defenders.

Prior to entering the I school, Rachel worked for five years as a data scientist in the private sector. Most recently she worked on the Salesforce Einstein team, where she helped develop a low code, automatic prediction engine, working specifically on a pipeline to help detect gender bias in customer models. She is the co-author of the O'reilly book, High Performance Spark.

Last updated:

April 16, 2024