Home » A Statistician's Life, Celebrating Women in Statistics

Rachel Schutt

1 March 2018 2,587 views No Comment

Affiliation
Managing Director at BlackRock where she leads Data Science together with Sherry Marcus.

Educational Background
Columbia University: PhD, Statistics (2009)
New York University: Master’s Degree, Mathematics (2003)
Stanford University: Master’s Degree, Engineering-Economic Systems and Operations Research (1999)
University of Michigan: Bachelor’s Degree, Honors Mathematics (1997)

About Rachel
Rachel Schutt was the Chief Data Scientist of News Corp where she oversaw the company-wide data strategy as an executive on the senior technology leadership team. There she established the company’s first data science team for Dow Jones, the Wall Street Journal, and other brands. Schutt was named a World Economic Forum Young Global Leader in 2015 and is on the 2014 Crain’s New York Business 40 under 40 list.

She has also been at the forefront of data science education. While working at Google Research (2009–2012), she recognized an emerging skill set (hybrid software engineer-statistician) was required. This skill set was not being taught in universities because it spanned traditional departmental lines and represented a new space of engineering, computational, and statistical problems coming out of technology companies. So to train the next generation of data scientists, Schutt proposed, designed, and taught the first Introduction to Data Science course at Columbia University (and one of the first such courses in the country). This course became the basis for the book she co-authored with Cathy O’Neil, Doing Data Science, published in 2013. Other university curricula now reflect the initial structure and content of her course. She is a founding member of the Education Committee for the Data Science Institute at Columbia.

While at Google Research, Schutt was part of the machine learning group in New York and holds patents based on her work in social networks, large data sets, experimental design, and machine learning.

Schutt is on the advisory board for Harvard’s Institute for Applied Computational Science (IACS).

She was born in Boston, Massachusetts, in 1976 and grew up in Cambridge, England, and Princeton, New Jersey. She was interested in math starting at a young age and found solving problems and puzzles fun and calming. When she was five years old, her father realized the girls at her primary school were being directed to practice knitting while the boys solved math problems. He intervened and came to the class to teach set theory to the girls. Schutt’s interest in math persisted throughout college, where she studied theoretical math. She worked for several years in a variety of jobs, and then—after having a chance conversation with Andrew Gelman—she returned to earn her PhD in statistics. Gelman became her adviser at Columbia along with Regina Dolgoarshynnikh. Schutt’s thesis work was on the spread of contagious processes in networks.

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