Mathematical & Computational Science: The Data Science Major
Welcome!
Since the 1970's, Mathematical and Computational Science (MCS) has been Stanford's home for students interested in deploying analytical and quantitative thinking to tackle problems in science, industry, and society. Increasing data size and availability, enhanced computational power, and progress in algorithms and software make this an ever exciting area.
Thanks to the common courses and faculty across four departments, MCS students acquire a solid foundation in mathematics, computer science, probability, statistics and optimization. They then explore how inferential and computational thinking can be effective in areas as diverse as finance, biology, marketing, engineering, etc. Or they can choose to acquire greater depth in one of the core disciplines.
Every year, our students continue to pursue their passions in a variety of positions in industry and academia.
Questions regarding the Program can be emailed to the mcs-inquiries [at] lists.stanford.edu (MCS Program Coordinator)
Why should students join the data science program?
The Data Science program is an amazing interdisciplinary program for students who are interested in exploring the intersection of various disciplines. The program not only establishes the technical foundation (statistics, computer science, and math) required to address social problems but also cultivates nuanced perspectives to approach these problems in unique ways (i.e. causal inference and optimization).
- Janice Li, Data Science & Social Systems B.A. ‘24
Why should students join the data science program?
I loved the flexibility of the Stanford MCS program, especially the opportunity to take classes from the Statistics, Mathematics, MS&E, and CS departments. This interdisciplinary approach allowed me to combine technical skills from various fields, giving me a well-rounded perspective on data-driven decision-making.
- Emir Kirdan, MCS B.S. ‘24
Why should students join the data science program?
For a tight-knit community, working on project areas most interesting to you, and learning how to tell a story with results.
- Richa Upadhyay, Data Science & Social Systems B.A. '24
Events
Join us for a lunchtime Q&A with Lenny Bronner, senior data scientist at The Washington Post and MCS alum, as he shares post-election insights. Discover how data science shapes our understanding of elections, from live forecasting models to parsing voter data, and get your questions answered…