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Data Science (M.S.)

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All Majors Welcome!

Bridge the gap between theoretical knowledge and successful practical application with our master's degree in data science.

Virginia Tech's Master of Science in Data Science is a non-thesis degree that combines rigorous technical training with real-world projects, preparing graduates to navigate organizational complexities and translate data into action and value. The faculty’s extensive industry experience delivers a blend of technical expertise and industry understanding to give graduates a distinct edge.

With an M.S. in Data Science from Virginia Tech, you will stand out among the rest.

One degree, three options...

Choose Your Path

Our Degree

September 30th, 2025- Panel discussion at VirginiaAI: Charting the Future of AI in Virginia. A summit hosted by the Virginia Academy of Science, Engineering, and Medicine (VASEM), in Alexandria at the Virginia Tech's Academic Building One. (photo by Craig Newcomb/Virginia Tech)

Room full of individuals at lined up tables with large screen displays at front of the room.

Career Opportunities

Stand out among the rest

According to the U.S. Bureau of Labor Statistics, the demand for data scientists is expected to grow by 34% by 2034. Students pursuing the M.S. in Data Science will receive the perfect blend of practice and theory: a combination that will help set them apart in this booming career field.

Close-up of man standing in front of classroom display screens, pointing at information on screen.

Experiential Learning

Solve real-world problems

The M.S. in Data Science is a non-thesis degree taught by industry experts with decades of experience in the field of data science. Students gain hands-on, real-world experience through a Capstone project completed in the second semester.

July 21st, 2025 - A group of graduate student researchers with the Center for Ecosystem Forecasting collect water quality data at a reservoir in Roanoke. (Photo by Luke Hayes/Virginia Tech)

Students standing on a bridge in a reservoir, gathering information from their data equipment.

Interdisciplinarity

Explore beyond math, stats, and computer science

Students can choose from concentrations in economics, forest resources and environmental conservation, geosciences, and industrial and systems engineering to combine data science with domain knowledge.