Wash U Institute Aims To Train More Data Scientists Of Color | St. Louis Public Radio

Wash U Institute Aims To Train More Data Scientists Of Color

Sep 8, 2019

Washington University is spearheading a new effort to diversify the field of data science.

Beginning in 2020, the university will train faculty and grad students from across the country in how to use data science tools and methods. The three-year program will focus specifically on recruiting underrepresented minorities, including Latino, indigeneous and black scholars. 

The program aims to equip researchers with the skills they need to be successful in this rapidly changing field, said Odis Johnson Jr., professor of sociology and education at Wash U.

“Data science is really experiencing a revolution,” said Johnson, who is leading the program. “There are new technologies and methodologies, new software programs every year at a pace that challenges a faculty member’s ability to keep up.”

Data science is a catch-all term that encompasses finding and analyzing large data sets to better understand complex issues, like fighting wildfires and predicting the spread of contagious diseases

The field has grown swiftly in the past decade, yet its workforce still suffers from a lack of racial and gender diversity

Odis Johnson Jr., professor of sociology and education at Washington University, is leading the new institute.
Credit Washington University

To help address this gap, Johnson said the institute plans to invest in faculty of color because they are often the ones training and mentoring budding data scientists.

“We really are putting more of our effort into faculty because we recognize that will give us a more immediate change in the demographic composition of data scientists,” Johnson said.

Up to 75 researchers will participate in the intensive program.

As part of the recruiting efforts, Johnson said Wash U has partnered with historically black colleges and universities, Hispanic-serving institutions and tribal colleges and universities.

The Institute in Critical Quantitative, Computational and Mixed Methodologies is also working to create a diverse network of scholars who are specialists in quantitative and computational methods — and can mentor the next generation of data scientists.

The program has received $1.1 million in funding from several organizations, including the National Science Foundation and the Spencer Foundation. 

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