It’s an exciting prospect: a new major surfaces that can get a liberal arts graduate through the door of virtually any field or industry. It’s called data science, and St. Catherine University is positioned at its cutting edge.
The data science field sprang up out of a need to make decisions based on ever-expanding data in every imaginable field — from healthcare, artificial intelligence, languages, and political science, to astrophysics, business, sports, and more.
The need is so pressing that the job and recruiting site Glassdoor ranks data scientist as the third-best job in America in terms of median base salary, job satisfaction, and availability.
Data scientists are in high demand because they can address data so comprehensively. They collect, organize, analyze, visualize, and communicate massive data sets using several disciplines: math, computer science, and statistics.
“A lot of companies have a ton of data, but there’s no one to analyze it,” says Tori Hagstrom ’21, who will graduate this spring as one of St. Catherine University’s first data science majors. “It’s a really fresh, brand-new major throughout the entire country, and having St. Kate’s paving the way is really awesome.”
Assistant Professor Monica Brown, MS, is the chief architect of St. Kate’s new major. She arrived at the University in 2008 with a master’s degree in statistics and a passion to make the field more appealing and accessible to a broader range of students.
“I know statistics can be scary for a lot of people — particularly for young women who may not have been encouraged to think they can do it,” she says. “So the entry point into the newly developed statistics minor is an algebra-based course rather than a calculus-based course. You need that upper-level math and stats knowledge for sure, but you don’t have to start there.”
Her strategy worked — so well, in fact, that the course ended up serving as a springboard for her next step in the plan: creating an interdisciplinary statistics minor.
Later, as math department chair, Brown began considering how to equip Katies at an even higher level to meet the growing demand for data analysts. She expanded the new statistics program, combining it with math and computer science instruction, to create the new data science major.
St. Kate’s institutional advancement team assisted her in proposing the concept to the James J. Hill Foundation, and they responded with funding for the Mary T. Hill Director of Data Science position to honor the memory of the Hill family matriarch.
Brown now holds that position. And the program — just two years old — already has attracted some 15 data science majors. Brown dreams of further expanding it to include summer programs and a master’s degree, and she recently launched the Just Data Lab as a campus resource she envisions making available to the larger community.
In today’s world, Brown says, Katies need to be able to watch a TV commercial, read an article, or look critically at a graph, and understand the data presented in each. They should be equally confident in their ability to tell stories through data.
“With data floating around anywhere and everywhere,” says Brown, “it’s really hard to discern what’s accurately represented and what’s not. But you don’t have to be a statistics major or knowledgeable about programming to be wiser about what’s being thrown at you.”
That’s why she created Intro to Data Visualization, a course with no higher-level math or statistics prerequisites. It’s open to all students, infusing the liberal arts curriculum with the notion that everyone benefits from data literacy.
Brown prefers to think of data science as a toolbox. “It’s not something you do — but something you use to inform your work in other areas.”
That toolbox contains both math and technical skills — plus the capacity to collaborate across disciplines, enabling the practitioner to serve as a conduit for complex projects. In financial services, for example, data scientists assess and predict financial scenarios to keep financial advisors better informed to make decisions on behalf of their clients.
In retail settings, they track supply and demand so that buyers and supply chain managers can better manage inventories.
Data science is also fundamental to artificial intelligence (AI) — the software that seeks to replicate human thinking to respond and solve problems in areas as diverse as product development and national security.
In the public-policy realm, a data scientist could map COVID-19 mortality and morbidity rates with data on race, income level, and access to affordable housing in order to explore possible links between community inequities and health disparities.
A history scholar schooled in data science could write a program to find and analyze specific characteristics in ancient documents and create hypotheses about the document’s significance within a culture.