Location: Corvallis Campus (in person)
Start term: Winter 2026
Data Science, B.S.
New major in the Department of Statistics
Data Science, B.S.
New major in the Department of Statistics
Data that informs real solutions
From climate change to cancer research, data is changing how we see the world and how we solve its hardest problems. It uncovers patterns, guides better decisions and helps build a society that’s more informed and fair.
Whatever your field of interest, chances are that data science intersects with it:
- Health and life sciences: biomedical research, pharmaceuticals, public health analytics
- Environment and sustainability: climate modeling, renewable energy and resource management
- Business and technology: finance, software, e-commerce, artificial intelligence
- Policy and nonprofit: education, government agencies, community and advocacy organizations
The demand for people who can make sense of data is exploding. Knowing how to work with data makes you more capable and even more valuable to future employers. The Bureau of Labor Statistics projects 36% job growth from 2023 to 2033 – much faster than most fields. Salaries are strong because organizations everywhere need people who can find meaning in numbers.
Learning outcomes
Graduates of the data science major will be able to:
- Analyze and interpret data using statistical methods, computing skills, and other data science tools and technologies.
- Assess real-world data problems and propose analytical methods to achieve effective and socially responsible solutions.
- Communicate data findings clearly and effectively to diverse audiences, tailoring messages to ensure understanding and impact.
- Collaborate effectively within diverse teams, valuing different perspectives and fostering civil discourse to enhance problem-solving and project outcomes.
Sample courses
In Oregon State’s data science program, you’ll master both the technical and the social impact of working with data. The curriculum rests on four pillars: mathematics, statistics, computer science and social responsibility. You will build a strong foundation, then move into advanced courses and hands-on experiences that connect what you learn to real challenges and practice.
- DS 201: Intro to Data Science (winter) – a broad survey of core concepts, tools and real-world context
- DS 231: Python Programming for Data Science (spring) – builds your computational and analytical foundation that prepares you for independent projects
- DS 350: Data for Good – emphasizing responsible and equitable data use
- DS 495: Capstone Project – team experience solving real-world problems
Data science as a “double major”
The data science major pairs well with many fields, especially those with established options in life sciences, economics, and environmental economics and policy. Because its core courses in math, statistics and computer science overlap with other disciplines, students in biology, mathematics, economics, environmental sciences, engineering and business can often add data science as a dual major without delaying graduation (learn about dual majors vs. double degrees).
Adding data science strengthens quantitative and computational skills while deepening understanding in a student’s primary field. For a smaller commitment, the data science minor (anticipated Fall 2026) introduces essential tools that enhance majors across the sciences, social sciences, business and the arts.
Add the data science major
Interested in adding or changing your major to data science?
Current students
- Consider taking the following courses during this academic year. These will get you in good shape when the data science major launches. In Winter 2026, take DS 201: Introduction to Data Science and MTH 267: Linear Algebra for Data Science. Then in Spring 2026, take DS 231: Python Programming for Data Science. DS 201 also counts toward the university’s quantitative core requirement.
- Connect with your advisor to let them know what you’re planning.
Transfer students
- Take lower-division credits in math, statistics, data science and computer science at your current college. We are actively working with local community colleges, including Linn-Benton Community College, to ensure that courses like DS 201 are eligible for transfer.
Undergraduate research opportunities
A hallmark of the data science major is its capstone project (below), where students apply what they’ve learned to solve real problems. Working in teams, students integrate technical and domain expertise, produce a final report and presentation, and gain experience in reproducible, socially responsible analysis.
Beyond the capstone, data science majors can also engage in undergraduate research through College of Science programs such as SURE (Summer Undergraduate Research Experience) and LURE (Launching Undergraduate Research Experiences). Because the program is interdisciplinary, students have opportunities to collaborate on projects in biology, statistics, computer science, economics and environmental science — applying data science tools to real-world challenges.
Capstone Experience
Students will complete a capstone project that integrates technical and domain skills, producing a final report and presentation. Projects may involve industry partners or research labs and will stress reproducible analysis and responsible data use.
Curriculum
Students must complete a minimum of 180 credits including the Core Education, major requirements, and electives. The curriculum emphasizes hands-on data analysis and socially responsible practice within a flexible, interdisciplinary framework.
Major Core (72 credits approx.)
- Intro to Computer Science II (CS 162)
- Data Structures and Algorithms (CS 261)
- Intro to Databases (CS 340) Intro to
- Data Science and Python Programming (DS 201, DS 231)
- Foundation in Mathematics (MTH 231, MTH 251, MTH 252, MTH 267)
- Statistical Methods (ST 351 or ST 314, ST 411, ST 412)
- Statistical Theory (ST 421, ST 422)
- Machine Learning and Statistical Learning (DS 431)
- Data Visualization and Communication (ST 437)
- Ethics in Data Science (DS 350)
- Capstone Project in Data Science (DS 495)
Options (Choose one, ~24 credits)
Students may choose one of four specialized degree options, though choosing an option is not required. Work with your advisor to choose electives that work best for your interests. For current students, contact: statistics.offfice@oregonstate.edu. For prospective students, contact carol.mckiel@oregonstate.edu.
In the Advanced Data Science option, you'll focus on advanced computing, machine learning and statistical modeling. It provides a strong foundation in advanced theoretical concepts, preparing you for graduate studies in fields like data science, statistics and biostatistics.
Download a 4-year sample plan of the Advanced Data Science option (.docx)
The Life Science option prepares you to address biological, ecological or health-related challenges using data science techniques. This program provides you with a strong foundation in key life science areas, which you'll integrate with data analysis skills. You'll gain the tools needed to analyze complex biological systems, interpret ecological patterns, and contribute to advancements in health and environmental sciences.
Download a 4-year sample plan of the Life Science option (.docx)
The Economics option provides you with a strong foundation in economic theory and how it applies in the real world. This program is designed to equip you with essential analytical skills, foster critical thinking in both economics and data science, and develop a solid understanding of how economic principles shape the way decisions are made within different contexts.
Download a 4-year sample plan of the Economics option (.docx)
The Environmental Economics and Policy (EEP) option was developed in collaboration with OSU's Department of Applied Economics. The option provides you the essential knowledge and skills to apply data science techniques to challenges like environmental issues and economic modeling and policy analysis. You'll be prepared to take on complex data challenges found at the crossroads where economics and the environment meet.
Download a 4-year sample plan of the Environmental Economics and Policy option (.docx)
Frequently asked questions
Career prospects for data science graduates are exceptionally strong. The U.S. Bureau of Labor Statistics projects 35–36% job growth for data scientists through 2023–33, far faster than most fields. Demand spans nearly every sector, from technology and healthcare to business, government and the environment, as organizations increasingly rely on data to guide decisions.
Graduates are prepared to turn data into discovery and insight into action in healthcare, technology, sustainability, business, policy and every area where data drives progress. Some become data scientists, applying their skills across disciplines. Others work as data analysts, business intelligence specialists or research associates, or go on to graduate study in fields such as statistics, economics, bioinformatics or artificial intelligence.
Year one
- DS 101: Exploring Careers in Data Science
- DS 201: Introduction to Data Science
- DS 231: Python Programming for Data Science
- Core Ed: Communication, Media and Society
- Core Ed: Difference, Power & Oppression Foundations
Year two
- MTH 231: Elements of Discrete Mathematics
- MTH 251Z: Differential Calculus
- CS 162: Introduction to Computer Science
- Core Ed: Scientific Inquiry & Analysis
- CS 261: Data Structures
- MTH 252Z: Integral Calculus
- MTH 267: Linear Algebra for Data Science
- CS 340: Introduction to Databases
Year three
- ST 411/412: Methods of Data Analysis
- ST 421/422: Introduction to Mathematical Statistics
- DS 350: Data for Good
- DS 431: Statistical Learning for Data Science
- ST 347: Data Visualization
Year four
- Option or elective course
- DS 495: Capstone and Career: Data Science
Download a 4-year sample academic plan for the data science major (without degree option). (.dox)
The major is designed for on-time completion, with courses offered regularly and a clear sample four-year plan available. Many of the required lower-division math and computer science courses overlap with those in other science and engineering majors, helping transfer and double-major students stay on track for graduation.
Yes, you can double major in data science. The data science major pairs well with many fields, especially those with established options in life sciences, economics, and environmental economics and policy. Because its core courses in math, statistics and computer science overlap with other disciplines, students in biology, mathematics, economics, environmental sciences, engineering and business can often add data science as a dual major without delaying graduation. Adding data science strengthens quantitative and computational skills while deepening understanding in a student’s primary field.
For a smaller commitment, the data science minor (anticipated Fall 2026) introduces essential tools that enhance majors across the sciences, social sciences, business and the arts.
It’s relatively easy to switch into or add data science as a double major, especially during the first two years. The foundational coursework – math, statistics, computer science and general education – overlaps with many other majors in the sciences and engineering. Students who make the change later may need to complete a few additional upper-division courses in data science or statistics.
Yes, students may transfer lower-division credits in math, statistics, data science and computer science into the data science major. We are actively working with local community colleges, including Linn-Benton Community College, to ensure that courses like DS 201 are eligible for transfer.
AP credits can be applied toward this major, for example, to fulfill requirements like MTH 251 and MTH 252.
Yes. Students in the data science major may be part of OSU’s Honors College, combining honors coursework and research with their data science degree requirements.
Data science majors are eligible for College of Science scholarships as well as university-wide opportunities.
We currently do not offer any graduate program in data science at OSU. But students can participate in the Accelerated Master’s Program to earn their M.S. in Statistics. In addition, this program also prepares students to graduate programs in statistics, biostatistics, data science, AI etc.
Contact information
For more information, contact:
- Current OSU students: Statistics.Office@oregonstate.edu
- Future students: carol.mckiel@oregonstate.edu
