The Harvard Business Review once described the work of a data scientist as the "sexiest job of the 21st century." 

One University of Arizona data scientist looked at 10 universities in the United States to better understand what a job in data science really means today. 

Jeffrey Oliver, a data science specialist at the University Libraries, is lead author of a recent research article in PeerJ Computer Science that investigates how well undergraduate training is aligning with the expectations for data science careers. 

The Conversation, an independent, not-for-profit news source committed to communicating the work of scholars, published a second article that Oliver and co-author, Torbet McNeil, wrote about their research findings: Data science education lacks a much-needed focus on ethics.

Data science education is a huge growth area right now.

“A wide range of industries that rely on predictions are using data science, and the need is growing,” said Oliver, who works in the libraries’ Research Engagement department (formerly the Office of Digital Innovation & Stewardship). He also leads the department’s Data Cooperative team and is involved in initiatives across the campus and at the University Libraries that are supporting data science initiatives for faculty and students.

The Data Science Institute, for example, offers collaborative research project opportunities, programs, courses, and resources for current and future data scientists. In 2020, Research Engagement launched the Research Data Repository for “non-traditional scholarly outputs resulting from research activities by University of Arizona researchers.” The library department also hosts the Data Visualization Challenge to engage and inspire students to communicate data to different audiences in visual and innovative ways.

The university is committed “to promoting not just the ‘doing’ of data science, but the data science training as well campus-wide,” Oliver said.

“Providing opportunities for faculty and students to really level up in their data science capabilities is the key.” 

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Data & Viz Drop-in
Tuesdays, 9-11am
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