Dr. Rachel Schutt is a Senior Research Scientist at Johnson Research Labs. Prior to that, she was a Senior Statistician at Google Research in the New York office. She is also an Adjunct Assistant Professor in Columbia’s Statistics Department, and is a founding member of the Education Committee for the Institute for Data Sciences and Engineering at Columbia. Rachel is co-authoring a book (with Cathy O’Neil) called “Doing Data Science” to be published by O’Reilly in 2013.
Her interests include statistical modeling, exploratory data analysis, machine learning algorithms, and social networks, as well as the ethical dimensions of Data Science, and using Data Science to do good. She holds several pending patents. She is a frequent speaker at conferences and universities.
She earned her PhD from Columbia University in Statistics, and Masters degrees in Mathematics and Engineering from the Courant Institute (NYU) and Stanford University, respectively. Her undergraduate degree is in Honors Mathematics from the University of Michigan.
In the Fall of 2012, she taught Introduction to Data Science (Statistics W4242) at Columbia University. This is the blog she wrote for that class. An interview with her on the Google Research page about Data Science and why she created the class in the first place can be found here. The course blog includes weekly reports on the lectures, as well as student work, and blog posts about Data Science.
Here is Rachel’s TEDx talk from December, 2012. The event organizers invited her to tell a personal story in order to embody one of 10 core tenets of leadership, so this isn’t a technical talk, but rather addresses how data and humanity go hand in hand. Also, after the semester wrapped up, the New York Times published this article by Steve Lohr, “Big Data is Great. But So Is Intuition“, which captures some of the themes of the course.