Computational Modeling & Data Analytics (B.S.)
LEARNING FROM DATA
Discover what we do with
Computational Modeling & Data Analytics
Computational Modeling and Data Analytics
The Computational Modeling and Data Analytics (CMDA) program draws on expertise from three primary departments at Virginia Tech with strengths in quantitative science: Mathematics, Statistics, and Computer Science. By combining elements of these disciplines in innovative, integrated courses that emphasize techniques at the forefront of applied computation, we teach a rich suite of quantitative skills for tackling today's massive data-based problems.
Data visualization class held in the Athenaeum classroom in Newman Library.
What can you do with a CMDA degree?
The CMDA requirements give students the flexibility to dive deeply into a particular area through choice of electives, a disciplinary track, or a minor or double major. Ultimately, our program is for anyone who seeks to better understand the world through data and computation.
Career Opportunities
- Environment / energy / sustainability
- Management consulting / government contracting
- Healthcare
- Banking / financial services / insurance
- Medical / biomedical / pharmaceutical
- Sports analytics
- National security / defense / space / crypto
- Design and manufacturing
- Big tech / cloud computing
- Media and marketing
- Public policy
Three students stand around a poster listing the external partners for the 2021-2022 CMDA Capstone Project Program. Photo by Julia Kell for Virginia Tech.
Want to work with us?
Become a Capstone sponsor.
Work with our undergraduate students to solve complex problems using data. Learn more about our Capstone program and other corporate partnership opportunities.
News
-
Article Item
Virginia Tech’s Academy of Data Science begins a new era , article Date: 07/01/2025 - -
Article Item
-
Article Item
Class of 2025: Yihan Liu builds his future on mathematical theory , article Date: 05/16/2025 -
Our Mission
CMDA educates principled data scientists who use their strong foundation in applied math, statistics, and scientific computing to solve problems of consequence that drive impact across society.