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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 ��ɫӰ�� 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.

“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.

Data science programs are springing up at colleges and universities around the country, but the St. Kate’s offering is unique in significant ways.

Similarly, according to the tech industry newsletter KDnuggets News, only about one-sixth of tech jobs are held by people from underrepresented groups (Hispanic or African American).

This lack of diversity can be dangerous, say the BCG researchers. The field of artificial intelligence, for example, is susceptible to bias because it selects data from sources that are inherently biased by historical and sociological factors. In addition, people who create AI algorithms and hypotheses can be influenced by unconscious bias — or worse — intentional bias.

The shortage of women and Black, Indigenous, and people of color (BIPOC) in the field makes it possible, even likely, that their contributions and needs will not be recognized in the data, and that critical projects and decisions will simply replicate injustices of the past. (One well-known example is the biased facial-recognition software used recently in Detroit to accuse a man of a crime he didn’t commit.)

��ɫӰ��, where the majority of undergrads are women and nearly 40 percent identify as BIPOC, is an obvious resource for employers seeking workforce diversity that can, in turn, help legitimize their data analysis in real-world applications.

That challenge is appropriate to graduates of ��ɫӰ��, where the institution’s curriculum and culture are rooted firmly in the social-justice legacy of its founders, the Sisters of St. Joseph of Carondelet — another major distinction.

In their junior or senior years, students in the major are required to take an upper-division class that offers a social-justice lens, such as critical race theory or women’s studies, so they learn to “not just do data science in a vacuum,” says Brown. “It helps them make that connection that we can use data science as a tool to address broad, systemic issues.”

As Dean Stanley puts it, “Previous generations interested in justice issues might have chosen something like law or social work. Now, here’s another thing you can choose to be deeply involved in to change people’s lives for the better.”

Offering data science in the context of a liberal arts education is another feature that distinguishes the St. Kate’s program from those offered at other institutions.

“Yes, data science is about data and numbers,” says Stanley. “But the glue that holds everything together is the way you think through it. Given the same set of numbers, one person will use them in one particular way that may not account for the nuances and differences that can seriously affect everything from school funding to well-being. But a person with a liberal arts background can interpret that data through multiple frames.”

St. Kate’s data science students learn those frames by way of a required second major or minor in another discipline — anything from art history to biology. They also pop up in the data science curriculum itself. Students can choose a generic statistics course or, depending on their career interests, one that’s offered in the context of healthcare, economics, or psychology.

Data science at St. Kate’s involves a heavy emphasis on communication, a traditional liberal arts skill that is essential in the endgame of any data sciences endeavor: clearly explaining what all this complex data means, telling a story through data, and creating data visualizations.

It’s her job to identify companies that hire graduates from particular majors, especially in Minnesota and the Midwest, and create opportunities for employers to connect with students in the classroom, through workshops, mentorships, internships, information interviews, and more.

According to Thao-Schuck, some of the top organizations hiring data science majors include 3M, UnitedHealth Group, IBM, Target Corporation, US Bank, Blue Cross and Blue Shield of Minnesota, and General Mills, and many of them are intentionally working to diversify their workforce. Opportunities also exist in finance, manufacturing, social assistance, transportation, public administration, utilities, and wholesale trade.

Along with the more traditional career development tools, students also compile résumés and portfolios that document the courses they take, the skills they’ve employed in the classroom, and co-curricular experiences. As Thao-Schuck says, “A degree alone doesn’t make you a qualified candidate. Employers hire skills.”

She describes the newly retooled career development process as “meeting students where they are,” as they first enter with their interests and ambitions, and partnering with them along a four-year career pathway that leads them to a job.

“The goal is for them to make the transition to their highest aspiration, whatever that is, and to find meaningful work and a purposeful life,” she says.

One good way to reach that goal is with a St. Catherine data science background — one that’s distinguished by academic excellence, framed through the liberal arts, and rooted in social justice.

By Mary Pattock ’66 from