Data science combines mathematics, statistics and computing to find patterns in data, make predictions and solve complex problems. From developing artificial intelligence and improving healthcare to understanding human behavior and responding to environmental change, data science is increasingly important across science, technology, business and society.
As a data science major at Oregon State University, you’ll build a foundation in mathematics, statistics and computer science while learning to analyze and visualize data, program in Python and R, work with databases, apply statistical and machine learning methods, and communicate what the data mean. You’ll also learn to consider the social and ethical implications of how data and AI are used.
You can tailor the major to your interests through options in Advanced Data Science, Economics, Environmental Economics and Policy, Life Science, and Psychological Science — or pair data science with another major. Combining data skills with expertise in another field can help you stand out in a job market where the ability to use data to solve problems is increasingly valued across industries.
Data Scientists are in high demand!
The Bureau of Labor Statistics shows strong demand for occupations that rely on data science skills. Data scientist is the fourth fastest-growing U.S. job, projected to grow 34% from 2024 to 2034. That’s 10 times faster than the average for all occupations.
B.S.
Degree needed for data science careers with the most growth
82.5K
Data science job projected to open yearly in the U.S.
What careers can you pursue with a data science degree?
Select a career pathway to learn more about pathways, common roles and the fields where data science is applied.
Career Pathways
Data science, AI and machine learning careers
Data scientists use statistical and computational methods to identify patterns, make predictions and extract useful information from complex data. Increasingly, this work intersects with artificial intelligence and machine learning, from developing predictive models to evaluating how AI systems perform.
As AI tools evolve, organizations will continue to need people who understand the data and statistical principles behind them — and who can determine whether models are accurate, appropriate and responsible for the problems they are intended to solve.
Pathway: All data science majors study mathematical statistics, Python and R, computer science, databases and data visualization. The Advanced Data Science option provides deeper preparation in algorithms, Bayesian modeling, and complex and network data, and is particularly useful for students considering graduate study in data or statistics. Students interested in machine learning, AI or more computationally intensive roles can also add a Computer Science minor or second major.
Common data science, AI and machine learning careers
- Data scientist
- Applied data scientist
- Machine learning engineers and analysts
- AI data specialist
- Statistical analyst
- Decision scientist
- Computer and information research scientist
Common employment sectors
Technology and software, scientific research, finance and insurance, health care, consulting, manufacturing, government
Data analytics and business intelligence careers
Data analysts help organizations make sense of information about customers, products, operations and performance. They may identify trends, create visualizations and dashboards, evaluate outcomes or translate complex findings into information that decision-makers can use.
These skills are needed across industries because organizations increasingly collect large amounts of data but still need people who can determine what the information means and how it should inform decisions.
Pathway: Coursework in statistical methods, programming, databases and data visualization provides preparation for analytics careers. Students can deepen their business expertise with a Business or Marketing minor, while the Applied AI in Business minor can support careers using AI and data-driven tools in organizational settings.
Common data analytics and business intelligence careers
- Data analyst
- Business and business intelligence analysts
- Product analyst
- Marketing analyst
- Operations analyst
- Research analyst
- Analytics consultant
Common employment sectors
Technology, retail and e-commerce, finance and insurance, consulting, health care, government, higher education, nonprofit organizations
Health, life sciences and bioinformatics careers
Data science is transforming how researchers and health organizations study biological systems, disease, treatments and populations. Large datasets from genomics, clinical research, public health and other areas create opportunities for people who can combine biological knowledge with quantitative and computational skills.
Data science professionals may analyze health outcomes, study genomic or biological data, support clinical research or help scientists identify patterns that would be difficult to detect using traditional methods alone.
Pathway: The Life Science option combines data science with a foundation in biology, preparing students to apply data science techniques to biological, ecological and health-related challenges. Students can build additional expertise with a minor or dual major in a biological science like Microbiology, Biology or Biochemistry and Molecular Biology — or with a Public Health minor. Undergraduate research will provide additional experience working with scientific data.
Common health, life science and bioinformatics careers
- Health data analyst
- Clinical data analyst
- Bioinformatics analyst
- Biostatisticians and biostatistics analyst
- Public health data analyst
- Research data analyst
- Computational biology research assistant
- Healthcare analytics specialist
Common employment sectors
Biotechnology and pharmaceutical companies, healthcare systems, public health agencies, universities and research institutes, government research agencies, health technology companies
Economics, finance and business analytics careers
Businesses, financial institutions, consulting firms and government agencies use data to forecast demand, understand markets, evaluate risk and improve decision-making. Professionals in these fields may analyze economic trends, model financial outcomes, evaluate business performance or use data to help organizations determine how to allocate resources.
Pathway: The Economics option is an excellent fit for students interested in understanding how economic principles shape decisions. Students can pair Data Science with an Economics dual major for deeper economic preparation or add a Finance minor (for financial and risk analytics) or a Business minor (for broader business interests).
Common economics, finance and business careers
- Economic data analyst
- Business analyst
- Financial data analyst
- Operations research analyst
- Quantitative analyst
- Risk analyst
- Pricing analyst
- Forecasting analyst
- Analytics consultant
Common employment sectors
Financial services, insurance, consulting, technology, government, retail and e-commerce, manufacturing, research organizations
Environment, sustainability and public policy careers
Data scientists can help researchers, governments and organizations understand environmental change, manage natural resources and evaluate the effects of public policies.
Professionals working in these areas may analyze climate, energy, economic, geographic or natural resource data to study questions involving sustainability, conservation, land use, environmental risk and policy.
Pathway: Combine data science with environmental economics, modeling and policy analysis with the Environmental Economics and Policy option, developed in collaboration with Oregon State’s Department of Applied Economics. The Life Science option can also prepare students to analyze ecological data and complex biological systems. For even deeper preparation, a Geography minor, GIS certificate or Geography and Geospatial Science dual major support spatial data careers, while the Sustainability minor, Public Policy minor, or Environmental Sciences dual major careers centered on policy and regulation.
Common environment, sustainability and public policy careers
- Environmental data analyst
- Sustainability analyst
- Policy analyst
- Natural resources data analyst
- Economic analyst
- Research analyst
- Program evaluation analyst
- Geospatial and GIS analysts
- Government data analyst
Common employment sectors
Environmental agencies, federal, state and local government, natural resource organizations, energy and utilities, research institutes, consulting, nonprofit organizations, universities
Human behavior, UX and organizational analytics careers
Understanding data about people requires understanding people themselves. Data science is increasingly used to study how people interact with products and technology, make decisions, learn, work and respond to different experiences.
Professionals working at the intersection of data and human behavior may conduct user research, analyze product or workforce data, study human-computer interaction or help organizations design technologies and services around how people actually behave.
Pathway: The Psychological Science option combines data science with the study of cognition, decision-making and behavior. Students can also consider a User Experience Research minor or a Psychology minor or second major for additional preparation in behavioral and user research.
Common human behavior, UX and organizational analytics careers
- UX researcher
- User research analyst
- People analytics analyst
- Organizational data analyst
- Product analyst
- Behavioral data analyst
- Customer insights analyst
- Human-computer interaction researcher
Common employment sectors
Technology, business, health care, education, consulting, consumer research, human resources and workforce analytics, research organizations
Research careers
Modern scientific research increasingly depends on the ability to analyze large and complex datasets. Data science methods are used across biology, environmental science, physics, engineering, economics, psychology and many other disciplines.
Data science professionals working in research may build models, analyze experiments, develop computational methods or help interdisciplinary teams identify patterns and test hypotheses.
Pathway: Students can combine data science with undergraduate research and a second major in any discipline where they want to conduct research. The Advanced Data Science option provides additional theoretical and computational preparation for graduate study and advanced quantitative research. Graduate education is commonly required for research scientists and other advanced or academic research careers.
Common research careers
- Research data analyst
- Scientific programmer
- Computational research analyst
- Quantitative research assistant
- Research associate
- Research scientist
Common employment sectors
Universities, government research laboratories, scientific research institutes, technology companies, biotechnology and health research, environmental research, engineering and advanced technology
Career Preparation
Related career paths across the College of Science
Data science overlaps with many other majors in the College of Science. Mathematics and statistics both provide foundations for quantitative analysis and modeling, while biology, chemistry, physics and other sciences provide important areas where data science can be applied.
Because data science is inherently interdisciplinary, students can use an option, minor, research experience or a second major to develop expertise in additional fields. The program is designed to pair particularly well with disciplines such as biology, mathematics, economics, environmental science, engineering and business.
Common questions
Skills developed through Data Science coursework and related hands-on experiences include:
- Statistical analysis
- Python programming
- Data management and databases
- Data visualization
- Statistical modeling and machine learning
- Evaluating uncertainty
- Data cleaning and preparation
- Reproducible analysis
- Evaluating models and interpreting results
- Responsible and ethical use of data
- Communicating technical findings
- Collaborative problem-solving
- Applying data science to real-world problems
Your coursework, degree option and experiences outside the classroom will all shape the skills you develop while at Oregon State.
Coursework builds the statistical, mathematical and computational foundation for data science careers. Beyond the classroom, experiences such as the senior capstone, undergraduate research, internships and independent projects help students apply those skills to real data and develop experience solving problems that do not have predetermined answers.
These experiences can also help students develop a portfolio of projects that demonstrates their programming, analytical and communication skills to employers or graduate programs.
Undergraduate research
Research can help you learn how data science is used to investigate questions that do not have predetermined answers.
Because data science intersects with many fields, students may contribute to research in areas such as:
- Biology and health sciences
- Statistics
- Computer science
- Economics
- Environmental science
- Psychology
- Other quantitative and computational fields
College of Science programs such as SURE Science, LURE and course-based undergraduate research (CURE) also provide opportunities for students to gain undergraduate research experience.
Research can be especially useful for students considering graduate school or careers in scientific research, advanced analytics, artificial intelligence and other highly technical fields.
Internships
Internships provide opportunities to apply data science skills to problems outside the classroom and learn how organizations collect, analyze and use data.
Potential internship settings include:
- Technology companies
- Research laboratories
- Healthcare organizations
- Biotechnology and pharmaceutical companies
- Government agencies
- Financial and insurance organizations
- Consulting firms
- Environmental organizations
- Universities and research institutes
- Nonprofit organizations
Internships can also help students build professional connections, explore different applications of data science and identify the skills employers value.
Other experiential learning
A hallmark of Oregon State’s data science major is its capstone project.
Working in teams, students integrate technical and domain knowledge to solve a real-world problem, producing a final report and presentation. Projects may involve industry partners or research laboratories and emphasize reproducible analysis and responsible data use.
Students can also gain experience through:
- Independent data projects
- Data competitions and hackathons
- Student organizations
- Research teams
- Interdisciplinary projects
- Community-engaged projects
- Leadership and professional organizations
These experiences can complement technical coursework by strengthening communication, teamwork and the ability to apply data science in unfamiliar settings.
Many careers in data science, analytics, business intelligence and related fields are accessible with a bachelor’s degree. The U.S. Bureau of Labor Statistics identifies a bachelor’s degree as the typical entry-level education for data scientists and operations research analysts. Employers may require or desire additional certification, programming experience, domain expertise or experience working with real data, which is why the data science major is designed to complement so many other programs at OSU.
Graduate education is more common in careers that require advanced specialization or original research. A master’s degree or doctorate may be beneficial or required for:
- Advanced artificial intelligence and machine learning research
- Statistics and biostatistics
- Bioinformatics and computational biology
- Advanced quantitative research
- University research and teaching
- Some economics careers
- Specialized scientific research
The Advanced Data Science option provides additional theoretical preparation for students considering graduate study in data science, statistics, biostatistics and related quantitative fields.
Because Oregon State’s data science major is new, common graduate-school destinations for program alumni are not yet available. The major provides ample preparation for advanced study across quantitative, computational and interdisciplinary fields. The best graduate program will depend on the area in which a student chooses to specialize.
Graduate disciplines to consider:
- Data science
- Statistics
- Biostatistics
- Computer science
- Artificial intelligence and machine learning
- Bioinformatics
- Computational biology
- Applied mathematics
- Economics
- Business analytics
- Environmental data science
- Quantitative social science
- Operations research
- Psychology and behavioral science
The Advanced Data Science option is specifically designed to provide stronger theoretical preparation for graduate study in data science, statistics and biostatistics. Other options allow students to combine data science with domain expertise that can support interdisciplinary graduate study.