OU Online Data Science Degrees: Which One Is Right for You?
by Michael Mahaffey
Table of Contents
Looking to advance your career in data analytics or data science? Choosing the right online master’s program is key to unlocking high-demand roles in a rapidly growing field. At OU Online, you can choose from four specialized master’s degrees–Econometrics, Applied Statistics, Business Analytics, and Data Science & Analytics–each designed to help you turn data insights into career impact.
Each flexible online degree is structured to support distinct career paths, academic goals, and skill sets. In a world where organizations are increasingly relying on data-driven decision-making, selecting the right program is a crucial step for applicants seeking a competitive advantage.
The data backs up the urgency. Employment of data scientists is projected to grow 36% from 2023 to 2033, according to the U.S. Bureau of Labor Statistics, far outpacing most industries. At the same time, more than 90% of organizations report measurable value from their analytics investments, according to a Coherent Solutions article.
In this fast-evolving landscape, the specialization you choose matters–whether econometrics, applied statistics, business analytics, or data science–can shape your direction in research, business strategy, or technology innovation.
Compare OU Online Data Science Master’s Degrees
Master of Arts in Econometrics: This degree is designed for students captivated by economics and policy research.
- Curriculum centers on mathematical modeling, economic analysis, and econometric theory—preparing graduates for roles in research, finance, government, and consulting
- Focus is on deeply understanding economic systems and using statistical modeling to explain trends and policy outcomes.
Master of Science in Applied Statistics: Perfect for students seeking versatility. Choose this degree for its breadth in statistical applications, from healthcare and politics to industry and research.
- The program delivers in-depth training in statistical theory, methods, and computing
- Graduates gain proficiency in tools like R, SAS, SQL, and hands-on, real-world consulting experiences, preparing them for careers as statisticians, biostatisticians, data analysts, and more.
Master of Science in Business Analytics: For those interested in applying analytics directly to business challenges, this program teaches how to harness data for strategic decisions.
- Coursework integrates business intelligence, visualization, forecasting, and data mining
- Practical approach uses tools like Python, SQL, NoSQL, and Tableau to prepare graduates for positions in business intelligence, data consultancy, and analytics management
Master of Science in Data Science & Analytics: This degree is for aspiring data scientists and engineers.
- Gain extensive technical skills in programming, machine learning, big data, and modeling
- Learn advanced tools and systems for extracting insights from massive datasets and building predictive models for technology-driven industries
Online Data Science Program Details and Career Options
| Degree | MA in Econometrics | MS in Applied Statistics | MS in Business Analytics | MS in Data Science & Analytics | Primary Focus | Economic/statistical modeling | Broad statistical methods | Business intelligence, analytics | Coding, modeling, big data |
|---|---|---|---|---|
| Skills Emphasized | Modeling, quantitative analysis | Statistics, research, software | Management Info Systems, Analytics Programming, Data Warehousing | Programming, Machine Learning, visualization |
| Typical Courses | Mathematical Economics, Econometrics, Data Science | Applied Statistics, Bayesian Statistics, R, SAS, SQL | Management Info Systems, Analytics Programming, Data Warehousing | Machine Learning, Big Data, Data Mining |
| Best Fit For... | Economics interests, policy, research | Diverse statistical applications | Applied business problem solvers | Tech-driven, hands-on, coding enthusiasts |
| Career Paths | Research/Financial Analyst, Economist | Statistician, Data Scientist, Analyst, Biostatistician | Business/Market Intelligence Analyst, Consultant | Data Scientist, ML Engineer, Software Engineer |
| Industries | Finance, Government, Academia | Healthcare, Insurance, Industry, Research | Business, Supply Chain, Finance, Marketing | IT, Tech Companies, Healthcare, Government |
Admission Requirements for Online Data Science Graduate Programs
- All programs require a bachelor’s degree from an accredited institution.
- Econometrics demands advanced statistics, linear algebra, and calculus coursework with a grade of B or better
- Applied Statistics recommends Calculus 1 and experience in R
- Business Analytics values a strong GPA or industry experience, with benefits for students with technical skills in writing code, use of complicated software or IT implementation
- Data Science & Analytics asks for a minimum 3.0 GPA and coursework in Calculus I & II, Linear Algebra, and one year of experience in high-level programming
Online Structure, Duration, and Tuition Costs
Each program is 100% online, but the program structure (live session frequency and synchronous/asynchronous mix) differs slightly across the programs. Completion time ranges from 16 to 24 months. Tuition for 2025-26 ranges from around $25,350 for Econometrics and Applied Statistics to over $33,000 for Data Science Analytics.
| Program Name | Credit Hours | Duration (Months) | Tuition (2025-26) | MA in Econometrics | 30 | 18 | $25,350 |
|---|---|---|---|
| MS in Applied Statistics | 30 | 21 | $25,350 |
| MS in Business Analytics | 32 | 16 | $32,480 |
| MS in Data Science Analytics | 33 | 24 | $33,495 |
Which Program is Right for You?
Econometrics: The MA in Econometrics is designed for students who want deep immersion in economic theory, modeling, and policy analysis. This program prepares you for serious quantitative research or policy work, typically favored by those with a love for economics and mathematics. Graduates are prepared for careers as economists, economic consultants, financial analysts, risk analysts, auditors, and more.
Applied Statistics: An MS in Applied Statistics will be the best fit if your interests span applying statistics to healthcare, industry, sports, or research. It is broad, with both theory and practical applications, and provides strong computing skills—suitable if you wish to be a statistician or data analyst across fields. Graduates can enter a broad range of careers, including statistician, data analyst, data scientist, market research analyst, data engineer, healthcare analytics, and more.
Business Analytics: The MS in Business Analytics is tailored for the data-driven business problem solver. This option is for those who want real-world, business-oriented projects that use analytics to inform strategy and improve efficiency. The curriculum is rich in business intelligence and prepares graduates to make impactful data-based decisions in the workplace. You’ll be ready for careers as varied as business systems analyst, business intelligence analyst, business consultant, analytics manager, market research analyst, computer systems analyst, and more.
Data Science & Analytics: The MS in Data Science & Analytics is ideal if you aspire to be a data scientist or machine learning engineer, aiming for roles that demand both coding and statistical skills for work with big data, AI, and predictive modeling. This program offers the most technical preparation in programming, database systems, and advanced analytics for fast-evolving tech-driven industries. You’ll be prepared for careers as a data scientist, data architect, data engineer, data modeler, database administrator, big data analyst, artificial intelligence engineer, machine learning engineer, and more.
Your ideal OU Online program depends on where you want to go, what you bring to the table, and how you learn best. Whether you’re ready to apply or want to learn more about which data analytics program is the best fit for your goals, our enrollment coaches are here to help. Explore each program in detail at online.ou.edu and take the first step toward your data-driven future.
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