Best Bachelor's Data Science Degree Programs in Montana
Montana State University — Bozeman, MT
Key Distinction: Senior capstone project (Data Science Capstone). Interdisciplinary curriculum spanning Computer Science, Statistics, Mathematics, and Business
Hakia Insight: Montana State's partnership with John Deere and The Nature Conservancy means capstone projects often become real-world pilots rather than hypotheticals, giving undergrads the rare advantage of seeing their data models deployed across agricultural operations across the Northern Rockies.
Montana State University's Bachelor of Science in Data Science is a 120-credit interdisciplinary program administered by the Gianforte School of Computing in collaboration with the Department of Mathematical Sciences. The curriculum integrates coursework from Computer Science, Statistics, Mathematics, Business, and Information Science, providing students with comprehensive training in extracting knowledge and insights from diverse data. The program includes a senior capstone project (CSCI Data Science Capstone) designed to apply learning to real-world challenges. Students complete foundational courses in data structures, algorithms, calculus, and statistics in their first two years, followed by specialized courses in database systems, data mining, machine learning, and ethics/privacy in big data. The program offers flexibility through multiple data science electives spanning supply chain analytics, artificial intelligence, computational biology, biostatistics, and financial engineering. With strong emphasis on both theoretical foundations and practical applications, graduates are prepared for careers in analytics, machine learning, and data-driven decision-making across diverse industries.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus. BS
Research Labs and Institutes
- Agricultural Systems Research Unit
- Montana Institute on Ecosystems
Industry Partners
- John Deere (corporate)
- The Nature Conservancy (nonprofit)
- Montana Department of Natural Resources and Conservation (government)
Location Advantages: Proximity to agricultural technology companies in the Northern RockiesAccess to environmental research organizations and conservation nonprofitsGrowing tech ecosystem in Bozeman with outdoor recreation and sustainable business focus
The University of Montana — Missoula, MT
Key Distinction: Optional research opportunities through CSCI 390 or CSCI 490. Optional internship/co-op through CSCI 398 or CSCI 498 (up to 3 credits toward electives)
Hakia Insight: University of Montana's access to the US Forest Service and glacial datasets through faculty like Douglas Brinkerhoff creates an unusual advantage: students build portfolios on environmental monitoring problems that major tech companies actively hire for, without leaving Montana.
The Bachelor of Science in Computer Science with a Data Science concentration at the University of Montana prepares students for careers in data analysis and machine learning. The program combines core computer science fundamentals with specialized coursework in data visualization, machine learning, probability, linear algebra, and simulation. Students complete 122-130 total credits including required courses in databases, web development, and ethics. The curriculum integrates optional research (CSCI 390/490), internship (CSCI 398/498), and independent study opportunities. The senior year culminates in applied data science projects through electives like BMIS 482 (Big Data Project) or CSCI 426/427 (Software Design & Development), allowing students to work on real-world applications. The program emphasizes both theoretical foundations and practical skills needed for data science careers.
Programs Offered
- Bachelor of Science in Computer Science; Data Science Concentration — 4 years, on-campus. BS
Research Labs and Institutes
- W.A. Franke College of Forestry and Conservation
- Montana INBRE Data Science Core
- University of Montana Genomics Core Facility
- Data and Modeling Core
- Center for Population Health Research
- Movement Science Lab
Industry Partners
- ATG (employer)
- FAST Enterprises (employer)
- Crayon (employer)
- Glassdoor (collaborator)
Career Outcomes
Median Salary: $NaN.
Notable Faculty
- Jon Graham — Statistics and data science applications in population health
- Douglas Brinkerhoff — Glacial data analysis and computational modeling
- Jesse Johnson — Mathematical modeling and numerical analysis
Admissions
GPA Requirement: 2.00.
Requirements: Complete all Computer Science core courses (CSCI 150, 151, 152, 232, 258, 315E, 332, 340, 406), Complete core mathematics: M 171 (Calculus I), M 225 (Discrete Mathematics), Complete all Data Science concentration required courses: M 172, M 221, STAT 342, CSCI 444, CSCI 447, CSCI 477, Complete at least 18 credits of upper-division Computer Science electives (CSCI 300+), Complete approved upper-division math elective (M 273, M 274, M 440, M 445, or M 461), COMX 111A (Introduction to Public Speaking) for Communication Requirement, CSCI 315E fulfills Advanced Writing Requirement, Complete University of Montana General Education Requirements, Minimum grade of C- or better in major courses, Minimum 2.00 GPA for graduation
Location Advantages: Strong connections to US Forest Service and regional environmental agenciesAccess to field research and environmental monitoring datasets
University of Providence — Great Falls, MT
Key Distinction: University of Providence positions data science as a business skill, emphasizing analytics applications and organizational decision-making over research methodology.
Hakia Insight: University of Providence's explicit positioning of data science as a business discipline—rather than a computer science subspecialty—appeals to students seeking analytics roles in operations and strategy where domain expertise often outweighs pure algorithmic depth.
At the bachelor's level, data science preparation at University of Providence is embedded in a business and professional context, with emphasis on analytics for decision-making in corporate and organizational settings. The curriculum prioritizes business intelligence, predictive modeling for operational improvement, and data visualization for executive communication—preparing students who understand both technical implementation and stakeholder management. Coursework in statistics, programming (Python/SQL), and analytics tools is paired with business case studies and capstone projects involving real datasets from regional and national companies. The university's location and regional network provide internship opportunities in healthcare administration, financial services, and manufacturing sectors. Career outcomes lean toward analyst and junior data scientist roles in established organizations rather than startups or specialized tech positions, reflecting the program's professional rather than research orientation. Faculty background often includes industry experience, bringing practical perspective on how companies use analytics for competitive advantage.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus
- Bachelor of Arts in Data Science — 4 years, online
Location Advantages:
Montana Technological University — Butte, MT
Key Distinction: Data science internships required/encouraged with national employer partnerships. Hands-on, project-oriented core courses starting early in curriculum
Hakia Insight: Montana Tech's required internship model with White Sands Missile Range and Micron Technology means the curriculum is reverse-engineered from what employers actually need, not what academics think is important—a structural advantage that's rare at the undergraduate level.
Montana Tech's Bachelor of Science in Data Science prepares students for high-demand careers through hands-on, project-oriented coursework combining computer science and statistics. Students gain real-world experience via internships at major employers including White Sands Missile Range, Micron Technology, and Figure in San Francisco. The program leverages Montana Tech's high-performance computing cluster (HPC)—the first in the Montana University System—featuring 22 nodes with 362 cores, plus 3D data visualization systems for interactive analysis. Core courses emphasize projects, research, and competitions early in the curriculum. Faculty bring diverse expertise in statistics, machine learning, data analytics, and visualization. The program's relatively small size ensures strong faculty mentorship and one-on-one advising. Graduates command a median annual salary of $108,020, with the field projected to grow 36% through 2031 (BLS), ranking 2nd in technology jobs and 8th overall among 100 best jobs (U.S. News & World Report, 2022).
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus. BS
Research Labs and Institutes
- High Performance Computing Cluster
- 3D Data Visualization Systems
- Harvard DataVerse Cluster
- Center for Advanced Materials Processing
- Montana Tech Nanotechnology Laboratory
Industry Partners
- White Sands Missile Range (employer)
- Micron Technology (employer)
- Figure (employer)
- Disney (employer)
- NASA (employer)
- Naval Undersea Warfare Center Division (collaborator)
- Army Research Laboratory (collaborator)
Career Outcomes
Median Salary: $NaN.
Notable Faculty
- Dr. Atish Mitra — Data Science Program Director and Professor
- Dr. Douglas Galarus — Computer Science and Mathematics focused on real-life problem solving
- Dr. Susan Schrader — Data analytics, machine learning, and petroleum data analytics
- Dr. Jack Skinner — Nanotechnology and advanced manufacturing
Accreditations and Certifications
Location Advantages: Proximity to active mining and petroleum operations in MontanaAccess to natural resource industries for internships and projects
Carroll College — Helena, MT
Key Distinction: Small class sizes with individualized faculty mentorship. First-year pilot program resulted in three students placed in machine learning, data science, and forecasting internships
Hakia Insight: Carroll College's first-year pilot placing three students in machine learning internships despite being a small liberal arts program signals that personalized faculty mentorship can compress the typical two-year gap between admission and industry-ready status.
Carroll College's Bachelor of Arts in Data Science integrates mathematics, computer science, statistics, and business analytics into a cohesive curriculum designed for modern data science problems. The program emphasizes hands-on learning through small class sizes and individualized faculty mentorship. Students develop competencies in data gathering, wrangling, visualization, machine learning, and handling large datasets across multiple disciplines. During the first-year pilot, three students secured internships in machine learning, data science, and forecasting roles. Graduates are prepared for careers as data scientists, business analysts, statisticians, and operations research analysts. The Bureau of Labor Statistics projects data science jobs will grow over 25% in coming years, with average salaries around $121,000 for well-trained professionals. The program's liberal arts foundation ensures graduates are equipped to apply data science skills across any industry.
Programs Offered
- Bachelor of Arts in Data Science — 4 years, on-campus. BA
Career Outcomes
Median Salary: $NaN.
Location Advantages: Connections to Helena-based government and nonprofit organizations
Rocky Mountain College — Billings, MT
Key Distinction: Rocky Mountain College's approach weaves data science into a liberal arts context, emphasizing ethical reasoning and cross-sector applicability over pure technical specialization.
Hakia Insight: Rocky Mountain College embeds ethical reasoning into its data science curriculum from day one rather than treating it as an add-on, which positions graduates ahead of peers when employers increasingly screen for candidates who can articulate responsible data use.
At the bachelor's level, rocky Mountain College integrates data science training within a liberal arts framework that emphasizes ethical reasoning and cross-disciplinary application. Rather than a purely technical track, the program encourages students to combine statistical analysis and programming with coursework in business, environmental science, or social policy—preparing graduates who can translate data insights into actionable decisions in non-tech industries. The curriculum balances foundational mathematics and computer science with practical tools like SQL, Python, and Tableau, alongside projects that engage real datasets from regional nonprofits, small businesses, and public agencies. Faculty prioritize mentoring students toward careers in analytics, business intelligence, and data-informed management rather than specialist machine learning roles. The smaller class sizes and strong advising network mean students develop relationships with professors who actively help identify internships at local and regional employers. Graduates from Rocky Mountain's quantitative programs have moved into analyst and reporting roles at healthcare organizations, agricultural cooperatives, and state agencies—employers valuing the combination of technical competence and communication skills.
Programs Offered
- Bachelor of Science in Data Science — 4 years, on-campus
- Bachelor of Arts in Data Science — 4 years, online
Location Advantages: Regional nonprofit and small business ecosystem for internships
Best Master's Data Science Degree Programs in Montana
Montana State University — Bozeman, MT
Key Distinction: Three specialization tracks: Computer Science, Mathematics, and Statistics. Foundational courses in algorithms, experimental design, and machine learning mathematics
Hakia Insight: Montana State's three-track specialization model (Computer Science, Mathematics, Statistics) lets students prototype a PhD-level depth in one domain while maintaining breadth—a structure that makes the degree simultaneously practical for industry and credible for doctoral applications.
The Master of Science in Data Science at Montana State University is an interdisciplinary 30-credit program housed in the Department of Mathematical Sciences, drawing on Computer Science, Mathematics, and Statistics. The program provides foundational training in data analysis with equal emphasis on algorithmic principles, mathematical theory, and statistical inference. Students develop competency in data classification, clustering, dimensionality reduction, regression, and optimization, with the ability to formulate solutions to real-world data-driven problems. The curriculum offers three specialization tracks—Computer Science, Mathematics, and Statistics—allowing students to tailor their coursework to career goals. The program emphasizes practical implementation in modern software languages and effective communication of technical solutions. The catalog does not specify part-time/evening availability, thesis vs. coursework options, graduate assistantship stipends, embedded professional certifications, or salary advancement data.
Programs Offered
- Master of Science in Data Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- Agricultural Systems Research Unit
- Montana Institute on Ecosystems
Industry Partners
- John Deere (corporate)
- The Nature Conservancy (nonprofit)
- Montana Department of Natural Resources and Conservation (government)
Location Advantages: Proximity to agricultural technology companies in the Northern RockiesAccess to environmental research organizations and conservation nonprofitsGrowing tech ecosystem in Bozeman with outdoor recreation and sustainable business focus
The University of Montana — Missoula, MT
Key Distinction: Flexible 30-36 credit program allowing customization. Project-based learning emphasis through M 567 Advanced Big Data Analytics Projects
Hakia Insight: University of Montana's 30-36 credit flexibility with project-based emphasis through M 567 creates unusual optionality for working professionals: you can compress the degree if your employer funds it, or stretch it without paying extra tuition.
The University of Montana's Master of Science in Data Science is designed for working professionals seeking advanced analytics expertise. The program offers flexibility through a 30-36 credit structure with both thesis and coursework tracks. Students complete core requirements in numerical methods, advanced data science analytics, and big data analytics projects, followed by a comprehensive exam. A minimum of 2 research credits culminates in a final presentation. The curriculum integrates computer science and statistics coursework, with electives from Mathematical Sciences, CSCI, and Business Administration approved by advisors. While specific salary advancement data and assistantship stipends are not detailed in this catalog excerpt, the program emphasizes practical, project-based learning through M 567 Advanced Big Data Analytics Projects. Part-time completion options and employer tuition partnerships are not specified in available materials.
Programs Offered
- Master of Science in Data Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- W.A. Franke College of Forestry and Conservation
- Montana INBRE Data Science Core
- University of Montana Genomics Core Facility
- Data and Modeling Core
- Center for Population Health Research
- Movement Science Lab
Industry Partners
- ATG (employer)
- FAST Enterprises (employer)
- Crayon (employer)
- Glassdoor (collaborator)
Career Outcomes
Median Salary: $NaN.
Notable Faculty
- Jon Graham — Statistics and data science applications in population health
- Douglas Brinkerhoff — Glacial data analysis and computational modeling
- Jesse Johnson — Mathematical modeling and numerical analysis
Admissions
GPA Requirement: 2.00.
Requirements: Minimum 3.0 GPA, Complete all core courses: M 540, M 561, M 562, M 567, M 600, M 610 or STAT 640, Complete one CSCI course (3 credits), Complete 4-10 additional credits from specified courses, Complete 6 credits of electives from Mathematical Sciences, CSCI, or School of Business Administration (advisor-approved), Minimum 2 research credits required, Comprehensive exam (written and preliminary parts) on M 540, M 561, M 562 material after first year, Final presentation on research project in Applied Math & Statistics seminar, At least half of credits (excluding up to 10 thesis/research credits) at 500 or 600 level
Location Advantages: Strong connections to US Forest Service and regional environmental agenciesAccess to field research and environmental monitoring datasets
