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Inaugural BSDS Cohort is Only UVA Applied Sciences Major with Female Majority
In the Fall 2024 semester, the University of Virginia’s School of Data Science welcomed its first-ever cohort of data science majors. This BSDS offering completed the School’s suite of degrees: Bachelors, Masters, and Doctoral. The inaugural class, B.S. in Data Science Class of 2027, includes 75 students, with 57% of the class being female-identifying.
The College of Arts and Sciences has a 60% female and 40% male split, while the School of Engineering and Applied Sciences is 33% women. BSDS is the only applied sciences major at the University with a female-identifying majority. Applied Sciences comprise the “TEM” in STEM: technology, engineering, and mathematics. The biology major, which falls under the “S” for science, also boasts a female-identifying majority.
The School of Data Science’s female-identifying majority more closely reflects that of the general undergraduate enrollment, a proportion that School administrators worked hard to reflect within the BSDS major.
The majority is consequential not only within the School but also in the professional world. The World Economic Forum's Global Gender Gap Report 2024 revealed that “women remain underrepresented in STEM roles, comprising only 28.2% of the STEM workforce compared to 47.3% in non-STEM sectors. … In turn, they make up a fourth of non-STEM leaders, and only over one-tenth in STEM.”
The School consciously worked to make the BSDS major accessible, diverse, and rigorous. Brian Wright, associate professor of data science and program director of undergraduate programs, shared insights on the School’s journey to actualizing the major and ensuring its diverse curriculum.
On what the female-identifying majority in the first-ever BSDS cohort means to him, Wright said: “It's a culmination of four years' worth of work with a team of people all striving towards these broad goals. However, it's also the start of a process that we want to maintain, to make sure that data science has a healthy pipeline of students from a variety of backgrounds and experiences.”
Wright elaborated that the School inherited a lot of cultural ethos of the data science field into the program. “Much of the movement that propelled data science as a field was happening during a period of time that encouraged broader inclusion into STEM programs. We benefited from this but also were conscious of the way we designed the degree in order for it to be seen as a large tent that would be appealing to a broad cross-section of backgrounds and interests.”
Yet, Wright said there was no conscious effort to attain this majority: “There was a conscious effort to make the degree appealing to UVA students generally; we simply replicated the major female population already present at UVA.”
He attributed the program’s flexibility and variety of education pathways as the main reason for increased female-identifying enrollment. “We also created a welcoming and supportive culture, tried to mitigate unnecessary competition, and instead framed a community of learners all working together to support each other and succeed,” Wright said.
Moving forward, Wright outlined plans to make sure that female faculty and data scientists are present in the School to talk with students. Additionally, the School ensured that its undergraduate recruiting ambassadors were composed of students from a variety of backgrounds. “If students can see themselves in the field, that really does help,” he said.
One of these ambassadors has a unique intersection of education and interest in diversity in STEM fields. Alka Link, a Data Science and Women, Gender, & Sexuality Studies double major, shared how it feels to be in the inaugural class and represent innovations in STEM.
“It feels very empowering to have a female-identifying majority in the inaugural BSDS cohort. Since STEM fields have been historically male-dominated, seeing this shift towards greater gender diversity shows the progress that the data science field has made to become more inclusive and equitable,” Link described. “This is especially inspiring since it is taking place in my own community at my university.”
She then posited that increased enrollment can be accredited to the vast and diverse promotion of the program. The major was advertised all over Grounds and in STEM clubs and classes, which Link thinks empowered more female-identifying students to apply.
“I remember being in my lab for DS 1001, and I got help on my assignment from a female data scientist who worked for the school. This empowered me to apply to the major because seeing women within the field was comforting and made me believe that I belonged in this field,” Link said.
Link has plans for the intersection of her two majors, reflecting the School of Data Science’s goal to offer a data science program with varying and diverse applications. “I see these two fields intersecting in the ethical side of data analysis. WGS helps to uncover biases that shape society, and DS can provide tools to analyze bias in data and algorithms,” she said. “This intersection of the two fields ensures that we are being ethical and inclusive in our data practices.”
