When Andrew Hong ’25 entered Stanford, he didn’t feel that any of the majors were a good fit.

The sophomore teetered between multiple choices, with political science and symbolic systems, in particular, standing out, but none seemed like a perfect fit for his interests in “political behavior and political science through an analytical and computational lens.” But when Hong learned from a peer advisor that Stanford was going to launch a data science major in the fall, he was ecstatic.

“I was trying to combine [different] sciences, and [the major] just kind of materialized,” he said.  “There was no need to like double major; it fit what I was trying to do.”

At the end of September, Stanford’s School of Humanities and Sciences announced that it had launched a new major in data science, offering undergraduates B.A. and B.S. tracks. The major has replaced the mathematical and computational science (MCS) major, though currently-enrolled students in that program will be able to finish their degrees.

According to a press release, the world’s increased need for data science given the unprecedented quantities and kinds of data prompted the creation of the major, a space for an interdisciplinary approach to big questions.

“Stanford has been ahead of the curve when it comes to preparing our students to work in the field of data science,” Debra Satz, dean of the School of Humanities and Sciences, said in the release. “Now that data is being produced at unprecedented rates and researchers have greater access to information on people and populations, the way we train data scientists must evolve as well.”

School of Humanities and Sciences spokesperson Joy Leighton wrote in a statement that compared to peer institutions with data science programs, Stanford’s program is unique:

“It builds on a very strong tradition of excellence in data-driven research and in the education of people with the skills and mindset for data science,” Leighton wrote, adding, “It is designed both with a strong foundational core and with easy connections with multiple areas of application.”

Furthermore, Leighton added, the two-pronged approach of the B.S. and the B.A. aims to grow one community of students and faculty, while “making space for different emphases.”

“Currently, the B.S. focuses on the methodological disciplines that provide the foundation of data science in a rigorous and truly interdisciplinary manner,” Leighton wrote. “The B.A. allows students to combine their technical skills with the subject matter competencies in the social sciences that students need to apply data science to social problems. An interdisciplinary approach is fundamental to both the B.S. and the B.A.”

The two degree options share similarities — soon to be housed in the Stanford Data Science and Computation Complex, which is under construction along Jane Stanford Way — and both will “complete a shared and thorough core curriculum of mathematics, computer science, statistical inference, optimization and ethics,” according to the release. Students will also be required to complete a capstone project where they will apply the knowledge and skills they acquire, the release said. 

However, B.S. and B.A. offerings differ when it comes to their academic focus.

Statistics professor and B.S. faculty director Guenther Walther said the B.S. is geared toward those “interested in deploying analytical and quantitative thinking to tackle problems in science, industry and society.” Career paths could include information technology, finance and graduate school in a quantitative field such as computer science, statistics or economics, he said.

Though the data science program is interdisciplinary in its focus, Walther said the key components of the B.S. is coursework in statistics, mathematics, computer science and management science and engineering. 

“The goal of the major is to provide a broad and deep understanding of the foundations of the discipline,” he told The Daily. “By learning the theory behind data science, the students develop the capacity to contribute new methodology in a field that is evolving rapidly.”

A new course, DATASCI 120: “Data Narratives,” which will be taught in the spring, has been specially designed for the new major. The class will teach students to “refine their ability to communicate ideas and insights with data” and understand “how different data collection processes can influence the data themselves, and how to evaluate the reproducibility of their results,” Walther said.

As for the B.A. route, this path is ideal for students who “want to work at the intersection of data science and human or social systems, either in a company, in government or in the non-profit or philanthropic sector,” faculty director Jeremy Weinstein said.

Weinstein, a political science professor, added that the goal is to “position” students with the core skills of a data scientist and depth in the social sciences to allow one choose to specialize on a particular social problem, “bringing the toolkit and domain knowledge to bear through advanced classes and a multi-quarter practicum with an external partner.”

The gateway course, DATASCI 154: “Solving Social Problems with Data,” will likewise be offered in the spring. According to Weinstein, this class will show “what’s possible at the intersection of data science and the social sciences, with deep dives into social problems as diverse as political polarization, climate change and educational inequality.” 

He said the class develops two different mindsets for tackling social problems with data — one rooted in causal inference and the other in optimization — as a way of thinking through the courses students might want to take going forward in the major. 

Weinstein is also excited about a class being offered this quarter called DATASCI 54: “Data Science at Work,” a one-unit seminar that brings in data scientists from government, nonprofits and the private sector to share their career stories and perspectives. 

“I am just blown away by the student interest in this series, and the thoughtful questions people are asking about how to use these 21st-century superpowers to tackle some of the hardest problems our society confronts,” Weinstein said.

For students like Hong, who is pursuing the B.A., the major will go beyond teaching solely computer science and math with its emphasis in social systems as a required subplan. It is a necessity for Hong and his passion in political data and mapping elections to analyze election trends, racial disparities and voter turnout.

“I think that this new major, what that does with those requirements really encourages and excites data science students to [use] the skills [acquired] to solve social problems,” Hong said. “[They would] not just have the skills, but also a context of how to apply those skills to social problems or the ethics of data science.”