What is MBA in data science | Top 50 MBA in data science program

data science mba programs

There is an increase in the number of people who want to study data science course. This is mainly due to the increase in the importance of big data. Now businesses require managers who can analyze and understand the implications of the information collected. MBA in Data Science programs are helpful as it helps the students to gather, sort, and understand the implications of the data and then use the data to meet the goals. Due to the increased importance of Big Data, business schools are now offering specializations in MBA in data science. We have compiled a list of 50 data science MBA programs that you can go through before deciding on enrolling in one. 

What is an MBA in data science?

An MBA in data science is an MBA program that provides a combination of business management and analytical skills. It provides a deeper understanding of data science and how it can be used along with management skills to make better business decisions.

Importance of an MBA in data science

An MBA in Data science helps you to pursue a career in strategic planning, risk management, brand management, finance, and consulting. Data is said to be the new oil in the digital economy. Using data science, this data could be converted into a much more valuable asset. It could help in making important business decisions effectively. An MBA in data science will provide you be prepared for the jobs of the future. It will you in the technical interpretation of strategic planning and development. 

Required Skill Sets for an MBA in Data Science

  • Statistics and mathematics
  • AIML
  • R Programming
  • Business Strategy
  • SQL
  • Python Programming
  • Communication skills
  • Collaboration
  • Data Visualisation

Top MBA in Data Science Programs

  1. NYU Stern School of Business, New York University
  2. University of Notre Dame-Mendoza College of Business
  3. The Wharton School of the University of Pennsylvania
  4. HEC, Paris
  5. Temple University- Fox School of Business and Management
  6. Tepper School of Business, Carnegie Mellon University
  7. Georgia Institute of Technology- Scheller College of Business
  8. Emory University- Goizueta Business School
  9. NUS Business School, National University of Singapore
  10. Imperial College Business School
  11. University of Florida- Warrington College of Business Administration
  12. Rutgers Business School
  13. Cornell University- Samuel Curtis Johnson Graduate School of Management
  14. Boston University- Questrom School of Business
  15. F. W. Olin Graduate School of Business at Babson College
  16. Hult International Business School- Europe Campus
  17. Hult International Business School
  18. IE Business School
  19. Kelley School of Business, Indiana University Bloomington
  20. Purdue University-Krannert School of Management
  21. Hult International Business School- San Francisco Campus
  22. University of Toronto- Joseph L Rotman School of Management
  23. City University of New York
  24. Arizona State University
  25. York University- Schulich School of Business
  26. University of Pittsburgh- Joseph M Katz Graduate School of Business
  27. University of Calgary- Haskayne School of Business
  28. Southern Methodist University- Cox School of Business
  29. UNC Charlotte- Belk College of Business
  30. Nottingham Trent University- Nottingham Business School
  31. University of Alberta-School of Business
  32. Queen’s University- The Stephen J. R. Smith School of Business
  33. McMaster University- DeGroote School of Business
  34. Drexel University- LeBow College of Business
  35. Hult International Business School- Shanghai campus
  36. University of IOWA- Henry B Tippie College of Business
  37. The University of Texas at Austin-McCombs School of Business
  38. McGill University- Desautels Faculty of Management
  39. Amsterdam Business School
  40. Universiti Teknologi Malaysia- International Business School
  41. The University of Illinois at Urbana Champaign
  42. MIB Trieste School of Management
  43. The University of North Carolina at Chapel Hill
  44. The University of Chicago Booth School of Business
  45. Georgia State University- J Mack Robinson College of Business
  46. Cardiff Metropolitan University- Cardiff School of Management
  47. University of Georgia- Terry College of Business
  48. The University of Buffalo- School of Management
  49. George Washington University
  50. Stanford University

Eligibility for MBA in Data Science programs

An individual who wants to pursue an MBA in a data science program from any of the top 50 universities needs to keep the eligibility criteria in their mind. The candidate must have completed their bachelor’s in fields related to data science. Completing the bachelor’s in these fields helps you to understand the subjects taught at the MBA level at these educational institutions. If the candidate is from a non-English speaking country, they will have to take the English language proficiency test like IELTS or TOEFL. A minimal GPA of 3.5 or higher is required at the undergraduate level. 

A high GRE score is also preferred by some universities. Though this is not compulsory, an MBA in data science means that the candidate must have a strong base in understanding quantitative methods. The scores in the written test are also given equal importance by the universities.

Letters of recommendation and statement of purpose are also required to submit with the application. 

Course eligibility criteria for MBA in Data Science offered by Great Learning:

  • You are eligible if you have completed your bachelor’s degree from a recognised university.
  • You must have secured at least 50% marks or equivalent CGPA (45% in case of SC/ST) from a recognized university.
  • You can also apply if you are yet to appear for your final year exams.
  • People appearing for professional courses like CA, etc., can also apply, provided that they meet the eligibility criteria on the bachelor’s degree.

The top 5 benefits of MBA data Science course

  • Rich Learning Experience. 
  • The uniqueness of this course will help you stand out from the crowd during recruitment. 
  • Better Pay: You can expect a much better pay once you complete this program. 
  • Python/SQL and statistics skills.
  • Helps in effective decision making which will lead you to make great impact on business to produce significant results.

Can I do MBA after BSc?

Yes, you can do MBA after BSc. The minimum eligibility criteria for an MBA is a bachelor’s degree from a recognised university with a minimal GPA of 3.5 or higher(or, at least 50% marks or equivalent CGPA).

Careers after pursuing MBA in Data Science programs

Since this is a new profession with many job opportunities, many people are increasingly completing their MBA specializations in the field of Data Science. Data science experts are required in practically every field. They are not limited to just technology. 

Data scientist

They analyze raw data and process the information to find patterns that will benefit a company.

Machine learning engineer

They create data funnels and help to deliver different software solutions. They design and build machine learning systems and also responsibly run tests and experiments.

Machine learning scientist

A machine learning scientist works on researching the different approaches to data and algorithms to be used in different adaptive systems.

Applications architect

They track the behavior of applications that are used by businesses and the interaction with the users. They also design the architecture of the applications.

Enterprise architect

They responsibly align the strategy of the company with the technology to fulfill the objectives of the company.

Data architect

They provide data solutions that enable good performance and also design analytics applications for different platforms. They also help to improve the functionality and performance of the existing systems.

Infrastructure architect

They check whether the systems of the business are working optimally. They check whether it can support the development of different technologies.

Data Engineer

They are responsible for performing batch processing on stored or gathered data. They also build and maintain different data pipelines. 

Business intelligence developer

These developers design and develop strategies for assisting business users to find data quickly and make good decisions. They are tech-savvy individuals who use BI tools for a better understanding of the system by the user.

Statistician

They gather, analyze and interpret the data for understanding the trends to inform the companies for making better decisions. They also communicate the different findings from the data to the stakeholders, advise about different strategies of the company, and so on.

Data analyst

The data analysts are responsible for transforming and manipulating large sets of data to suit the needs of the companies. These individuals also track the web analytics and analyze A/B testing.

You can also expect job roles in other industries like: 

  • Consulting.
  • Information management services.
  • Research Industry.
RolesIndiaUS
Data Engineer8 LPA$1,12,493
Data Analyst5 LPA$65,055
Data Scientist10 LPA$74,943
Risk Analyst5 LPA$72,435
Business Analyst8 LPA$74,041
Statistician4 LPA$88,989
Business intelligence developer7 LPA$94,743
Data architect20 LPA$1,18,868

MBA in Data Science is much helpful for those individuals who want to pursue a career for themselves in the field of data science. Completing the MBA program will give them an idea about the various aspects of big data and they will be able to deal with it effectively at their workplaces. 

Want to take your learning journey to the next level? Check out the executive pg program in data science and upskill today!

→ Explore this Curated Program for You ←

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Great Learning Editorial Team
The Great Learning Editorial Staff includes a dynamic team of subject matter experts, instructors, and education professionals who combine their deep industry knowledge with innovative teaching methods. Their mission is to provide learners with the skills and insights needed to excel in their careers, whether through upskilling, reskilling, or transitioning into new fields.

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