Choosing between a Master of Business Administration (MBA) in Data Science and a Master of Science (MS) in Data Science comes down to one core question. Do you want to lead the teams that use data, or do you want to build the models yourself? By combining coursework in finance, marketing and strategy with hands-on training in database design, predictive analytics and business intelligence tools, Pittsburg State University’s online MBA in Data Science and Information Systems program, which is accredited by the Association to Advance Collegiate Schools of Business (AACSB), prepares business leaders to translate data into strategy. By contrast, an MS in data science trains graduates to design algorithms, build machine learning models and write the code that powers modern analytics systems.
Both paths attract professionals who want their careers to center on data, but they serve different ambitions. The MBA path suits managers, analysts and rising leaders who want to interpret data, communicate insights and guide decisions across an organization. The MS path suits technically minded professionals who want to build the systems, models and algorithms that generate those insights.
This guide compares the curriculum, career outcomes, salary potential and admissions requirements for both paths. Whether you already work in business intelligence or are ready to move from an individual contributor role into data leadership, understanding the differences will help you choose the program that best aligns with your goals.
MBA vs. MS in Data Science: How Does the Curriculum Compare?
Pittsburg State’s MBA in data science and information systems curriculum blends core MBA training with technical coursework. The program is specifically designed for working professionals looking to develop both business and analytical skills. Students complete the same foundational coursework in marketing, finance, strategy and organizational leadership that any MBA program offers. The concentration layers on courses in database design, predictive analytics and business intelligence, taught through tools business teams use every day, including SQL, Tableau and RStudio.
An MS in data science takes a narrower and more technical approach. Coursework concentrates on statistics, machine learning and programming languages such as Python and R, with less emphasis on business strategy or management training. Most MS programs also require a capstone project or thesis that demonstrates a graduate’s ability to build and validate a working model independently, a requirement that reflects the degree’s orientation toward individual technical contribution rather than team leadership.
The practical difference between the two curricula becomes clear when you compare what each degree asks a student to produce by graduation. An MBA graduate leaves with the ability to interpret a data science team’s output and turn it into a business decision, while an MS graduate leaves with the ability to build the model that produced the output in the first place.
- Pitt State’s MBA relies on SQL for querying business data, Tableau for visualization and dashboards, and RStudio for applied predictive analytics, all paired with MBA coursework in finance, marketing and strategy.
- An MS in data science relies on Python and R for statistical modeling, machine learning frameworks for building predictive algorithms, and advanced statistics coursework, typically with limited business curriculum.
Neither list should be read as a ranking of one path over the other. It simply reflects that the two degrees develop different professional skills for different roles in the data ecosystem.
Career Paths and Salary Potential for Each Path
Graduates of Pitt State’s AACSB-accredited online MBA in Data Science and Information Systems program may pursue leadership roles that sit at the intersection of business and analytics, such as business intelligence manager, data analytics manager and chief data officer. According to the U.S. Bureau of Labor Statistics (BLS), computer and information systems managers, the category that captures many BI and data analytics management roles, earned a median annual wage of $175,140 in May 2025, with employment projected to grow 16% through 2035, much faster than the average for all occupations. Compensation climbs further at the executive level. PayScale reports an average annual salary of $172,373 for chief data officers in 2026, with top earners surpassing $287,000, reflecting the premium organizations pay for leaders who can turn data strategy into business results.
Graduates of an MS in Data Science more often move into hands-on technical roles, most commonly data scientist, machine learning engineer or data engineer, where the work centers on building and refining models rather than managing teams. BLS projects data scientist employment to grow 35% from 2025 to 2035, among the fastest growth rates of any occupation the agency tracks, with a median annual wage of $120,230 in May 2025. That growth reflects rising demand for the professionals who build the predictive systems that MBA-trained leaders then use to make decisions, a reminder that the two career paths depend on each other even though they sit on opposite sides of the data pipeline.
Demand for both types of professionals remains strong across industries. O*NET Online designates business intelligence analysts, a common early-career title in the MBA track, as a Bright Outlook occupation, meaning the role is projected to grow rapidly and produce a high volume of job openings nationally. McKinsey & Company reports that demand for technology talent continues to outpace supply, with the gap projected to reach into the millions in the years ahead as organizations invest further in data and AI capabilities. Together, these trends suggest that whichever path you choose, the market rewards professionals who understand both the technical and strategic sides of data work.
What Each Program Expects From You in Admissions
Admissions requirements show one of the sharpest differences between the two paths. Pitt State’s online MBA in Data Science and Information Systems program does not require the GMAT or GRE for admission. The program instead weighs a combination of academic and professional readiness, considering at least three years of experience in a managerial role, or a recent bachelor’s degree in a business-related field, along with a minimum 2.7 GPA and a resume that reflects relevant experience.
This approach reflects a broader shift in business school admissions. The Graduate Management Admission Council (GMAC) tracks how business schools evaluate their applicant pools each year, and many MBA programs now weigh professional experience and academic performance more heavily than a single standardized test score. Programs that still require a test typically ask for the GMAT, the GRE or an equivalent assessment, though the requirement varies widely from school to school and often depends on whether an applicant already holds an advanced degree.
MS in data science programs generally take the opposite approach to admissions. Most require applicants to demonstrate a strong quantitative background through coursework in statistics, calculus or computer science, along with competitive GRE scores in many cases. Applicants without a technical undergraduate degree often need to complete prerequisite coursework before starting the program, which can add time and cost before a student ever begins the core curriculum. That additional barrier is one reason many business professionals with nontechnical undergraduate degrees find the MBA path more immediately accessible.
Who Should Choose the Data Science MBA Path vs. MS Path?
Choose the MBA if your goal is to lead people and strategy and choose the MS if your goal is to build the technology itself. Professionals who enjoy translating numbers into a story for executives, who want to manage teams and budgets, and who see themselves eventually running a data function rather than coding within one, tend to thrive in an MBA program centered on applying data to business strategy. The MBA path also suits professionals who already work in business, sales, marketing or operations and want to advance to leadership roles where data fluency is highly valued.
The MS path suits professionals who want to spend their days writing code, testing models and solving technical problems, with less interest in managing people or presenting to a boardroom. According to Harvard Business Review, organizations increasingly separate the work of interpreting data for decisions from the work of building the systems that generate it, and both functions carry significant career value. If you already have a strong quantitative background and want to specialize deeply in machine learning or statistical modeling, the MS is likely the better fit for your goals.
There is no wrong choice between the two, only the path that matches how you want to work with data. If you want to lead data-driven teams and combine business strategy with analytics fluency, Pitt State’s MBA in Data Science and Information Systems is designed for that role. If you want to build and deploy models yourself, an MS in data science offers the deeper technical training that path requires.
Gain Data-Driven Leadership Skills With an Online Data Science MBA From Pitt State
Pitt State’s MBA in Data Science & Information Systems program is designed for working professionals who want to develop data-driven leadership skills. Students can complete the program in as few as 12 months, a timeline made possible by an online format that lets you continue working while you study. The accelerated pace does not come at the expense of technical training. Coursework in SQL, Tableau and RStudio gives students hands-on experience with the same tools used by business intelligence and analytics teams at large organizations.
What separates the MBA program from a standalone MS in data science program is the combination of business and technical training. Every MBA student completes coursework in finance, marketing and organizational strategy along with data science concentration courses, preparing graduates for in-demand roles that require both business judgment and technical fluency, including business intelligence manager, data analytics manager and chief data officer.
Beyond the curriculum, Pitt State supports students with dedicated faculty who help translate advanced coursework into skills they can apply immediately on the job. Students who want broader expertise can add a second MBA emphasis by choosing from eight specialized areas, often with as few as three additional courses and, in many cases, just one extra semester. With no GMAT or GRE requirement and the same flat tuition rate for all students, the program helps learners move from application to graduation and toward stronger earning potential without the added time and cost many competing programs require.
Explore Pitt State’s online MBA in Data Science and Information Systems program and take the next step toward leading data-driven teams.
About Pittsburg State University
Pittsburg State University’s AACSB-accredited, 100% online MBA in Data Science and Information Systems program is designed for working professionals looking to advance into data-driven leadership roles without pausing their careers. The program pairs core business coursework in finance, marketing and strategy with a concentration in data science and information systems, giving graduates a business credential and specialized technical training in one degree.
Pittsburg State University was founded in 1903 and is located in Pittsburg, Kansas. The university enrolls more than 5,300 students and is classified by the Carnegie Foundation among Master’s Colleges and Universities, Larger Programs institutions. Its Kelce College of Business holds accreditation from AACSB International, a distinction held by a small share of business schools worldwide, and the college shapes its graduate programs around the same career-focused mission that defines the MBA in Data Science & Information Systems.
That commitment to career-focused education is reflected in outside recognition as well. The Princeton Review has repeatedly ranked the Kelce College of Business among the nation’s Best Business Schools, including a 2025 distinction as one of the Best Business Schools in the Midwest. Paul Grimes, Ph.D., dean of the Kelce College of Business, describes that standard directly: “There is a culture to being an AACSB-accredited school, and we [Pitt State] definitely demonstrate that.”
