Typical Class Profile
The Online M.S. in Data Science is a cohort-based program designed for high-achieving students interested in data science.
| Average Cohort Class Size | 30-35 |
| Age Range | 20-70 |
| Female-Identifying | 41% |
| First-Generation | 15% |
| LGBTQ+ | 7% |
| Military/Veterans | 12% |
| Number of Countries Represented | 14 |
| U.S. States and Territories Represented | 20 |
| Number of Undergraduate Institutions | 61 |
| Number of Undergraduate Majors | 42 |
| GPA Range | 2.4-40 |
| Received Need-Based Fellowship from the School of Data Science | 12% |
| Have Professional Work Experience | 88% |
Meet Online MSDS Students
“I want to get a technical sense of the real possibilities in data science so in the future I can build data tools to help understand and remedy issues of economic inequality.”
- Jordan Hiatt, MSDS 2022, Profit Optics, Business Analyst
“In the future, I hope to help power humanitarian and economic growth through ethical data collection to reach the world’s 1.7 billion unbanked and countless more underbanked individuals.”
- Loren Bushkar, MSDS 2022, Institute of Internal Finance, Managing Director
“I hope to learn more about the intersection of public policy, health, mental health, and justice and collaborate with a research and policy team to help understand and react to problems that feel too big to fathom.”
- Diana McSpadden, MSDS 2022, National Center for State Courts, Web Development Manager
“I hope to use data science in the future to solve complex business problems that require insight into the data.”
- Rehan Merchant, MSDS 2022, EY, Technology Risk Consultant
“I want to learn more about machine learning, performative text analysis, neural networks so I can create innovative applications to promote justice and create concrete, positive advancements for marginalized groups (esp. Black people).”
- Lauren Neal, MSDS 2022, Actor/Writer/Director/Producer
“I am most interested in expanding my technical skill sets and becoming a better analytical storyteller. I want to have the tools to tackle really difficult data and computational problems along with a strong ability to articulate my findings both verbally and in writing.”
- David Fuentes, MSDS 2022, UBS, Associate Director of Capital Management Reporting
“I am very interested in learning about the power of Machine Learning and Data visualization for large biological data sets.”
- Chelsea Alvarado, MSDS 2022, Howard Hughes Medical Institute's Janelia Research Campus, Connectome Annotator
“I’m interested in learning the technical side of data science and understanding the processes that happen under the hood of machine learning models.”
- Dylan Howe, MSDS 2022, Virginia Department of Transportation, Data Analyst