When Wendy Zhang ’26 graduates from Pomona College this spring, she will not only have completed a cognitive science major. She will also be one of the first Pomona students to fulfill requirements for the College’s new data science minor.
“I am interested in pursuing cognitive neuroscience, and data science is a necessary component,” says Zhang, who hails from Beijing. “It also prompts me to go beyond my comfort zone and obtain computer science and statistical fluency.”
Jo Hardin, Hardison Chair of Analytical Thinking and professor of mathematics and statistics, has been the guiding light for the new course of study, added to the College’s catalog in 2024. She leads a core advisory committee that includes professors from biology, computer science, economics, environmental analysis, linguistics, neuroscience and psychological science as well as math and statistics.
Ami Radunskaya, Lingurn H. Burkhead Professor of Mathematics, says that when Hardin first proposed the new minor, “I jumped on board right away. I think it’s a fantastic opportunity for our students.” She notes that “data is everywhere, and data science is just a way to build up the tools necessary to use that data effectively in whatever you’re doing.”
Ernesto R. Gutiérrez Topete ’17, visiting assistant professor of linguistics and cognitive science, also joined the advisory committee as soon as he heard about the proposed program and has been part of its development from the ground up.
Gutiérrez Topete says that data science is often associated with science, technology and math. “One of the things that the program has held as a priority since the beginning is to diversify the application of data science to expand outside of STEM disciplines,” he says. Whatever their major, “We want Pomona students to gain well-roundedness. This is a really great way they can do that.”
To complete the minor, students take five core courses: Linear Algebra, Introduction to Statistics, Introduction to Computer Science, Foundations of Data Science, and a relevant ethics class. They apply what they have learned in a capstone project with a faculty mentor. The capstone must be in a field outside of math, statistics and computer science.
Topics in the first capstone cohort ranged from creating a dashboard for personalized medicine to analyzing Ghana’s macroeconomic indicators to automating a baseball analytics system for Pomona-Pitzer athletes.
Zhang’s project, “Multiverse Analysis in Functional Magnetic Resonance Imaging Across Cognitive Tasks,” addressed the research question, “Do variations in the fMRI preprocessing and analysis pipelines change potential results?”
The project “bridged subject-specific skills with data science methods in a more organic way,” she says. It was “also an opportunity for reflection, as I was able to pinpoint the skills that I have developed as well as those that I aim to continue learning.”
Hardin says that when she interacts with people in industry, especially in the tech industry, “They often refer to evidence of potential hires ‘doing’ data science. That’s what they are looking for in hiring.” The capstone project, she tells students, is like “a portfolio that shows your skill set.”
Radunskaya says there is data in every field and would love to see students applying data science to a broad range of disciplines: “Art, music, anthropology—you name it,” she says.
“I’m excited to see our students go out and attack problems that are really important to society with the necessary tools to understand how to use and wrangle data properly,” she says. “Every possible problem in the world, we’re going to use data to try to understand and solve it.”