Is an MBA worth it after a Master’s in Data Science from Canada or Australia?

Asked by A.K Chaturvedi 7 months ago

4 Answers
Mansi Jain

Mansi Jain

Study Abroad Specialist

Hi A.K.,

Pursuing an MBA after a Master’s in Data Science from Canada or Australia can be worth it, depending on your career goals. Here are some reasons why:

  • Management Roles: An MBA degree can open up management roles such as Data Science Manager, CTO, or Product Manager, which is not possible with a Data Science degree.
  • Broader Skill Set: A Master’s in Data Science provides technical skills while an MBA equips you with skills in business strategy, marketing, finance, and management.
  • Higher Salary Potential: An MBA with a Master’s in Data Science degree can lead to higher-paying job opportunities, especially in senior positions.
  • Networking Opportunities: An MBA can expand your professional network, connecting you with peers and industry leaders, which can be valuable for career growth.

However, if your primary interest lies in technical roles, an MBA might not be the right choice. Pursuing an MBA after a Master's in Data Science can be a valuable step if you're aiming for leadership roles and a broader skill set. A study abroad expert can assist you in this journey by offering guidance on selecting the right programs, handling applications, providing financial options, and more.

 


upvote icon
Upvote0
Comment
0
Share

Hi,

Whether an MBA is worth it after a Master's in Data Science from Canada or Australia depends on your specific career goals and aspirations. Here's a breakdown of the potential benefits and drawbacks to consider:

Potential Benefits of an MBA:

  • Enhanced Career Prospects: An MBA can open doors to leadership and executive roles that might not be accessible with a Master's in Data Science alone.    
  • Improved Business Acumen: An MBA provides a comprehensive understanding of business functions like finance, marketing, and operations, which can be valuable for data scientists who want to move into strategic roles.    
  • Stronger Networking Opportunities: MBA programs offer excellent networking opportunities with peers, alumni, and industry professionals.    
  • Increased Earning Potential: MBA graduates, especially from top-tier programs, often command higher salaries.    

Potential Drawbacks:

  • Significant Investment: An MBA is a significant investment of time and money.    
  • Opportunity Cost: Pursuing an MBA means forgoing potential career advancement and earnings during that time.    
  • Potential Overqualification: In certain data science roles, an MBA might be considered overqualification, especially if the focus is on technical skills.

Key Considerations:

  • Career Goals: If you aspire to C-suite roles or want to transition into a more general management role, an MBA can be beneficial.
  • Industry Trends: The increasing demand for data-driven decision-making means that data scientists with strong business acumen are in high demand.    
  • Program Fit: Choose an MBA program that offers relevant specializations or electives in data science or analytics.
  • Return on Investment: Consider the potential return on investment (ROI) of an MBA, including the increased earning potential and career opportunities.

Ultimately, the decision to pursue an MBA after a Master's in Data Science is a personal one. Carefully weigh the potential benefits and drawbacks, and consider your long-term career goals to make an informed decision. 

I would suggest you to get free counseling from a study abroad consultant for applying for your desired universities and get in the right direction.


upvote icon
Upvote0
Comment
0
Share

Mohit C

Mohit C

Business analyst

An MBA can definitely be worth it after a Master’s in Data Science from Canada or Australia—but only if your goals shift toward leadership or business-facing roles.

After a data science master’s, most grads start in roles like Data Scientist, Machine Learning Engineer, or BI Analyst, with starting salaries in Canada around CAD 70K–90K and in Australia AUD 75K–95K.

These roles offer solid growth, but the ceiling can hit early if you're aiming for positions like Product Lead, Chief Data Officer, or Strategy Head—which typically require broader business understanding.

An MBA from schools like Rotman, Melbourne Business School, or even international programs like INSEAD or LBS positions you for mid-senior roles with salaries ranging from CAD 110K–150K+. It’s also valuable if you want to pivot into consulting (e.g., BCG, McKinsey) or tech product management, where MBAs are often preferred.


So, yes, it’s worth it—but only after gaining 2–3 years of real-world experience in data-focused roles. It’s less about “more education” and more about “career direction shift.”


upvote icon
Upvote0
Comment
0
Share

K S Saini

K S Saini

Education Expert

It depends on your goals. If you plan to stay in technical roles like Data Scientist or ML Engineer, an MBA may not be necessary. But if you want to transition into product management, consulting, or data-driven leadership, then an MBA can be a smart move.

For example, someone working in Sydney or Toronto earning AUD/CAD 90K as a data professional could move to roles paying 120K–150K+ post-MBA—especially in positions like Product Manager, Strategy Consultant, or Analytics Lead.

Top MBA programs like Ivey, AGSM, or even global ones like INSEAD offer strong post-MBA placement in these roles. Just make sure you have 2–3 years of work experience before applying—MBA ROI is strongest when done after solid industry exposure.

If the goal is to grow beyond the technical path and take on business-facing roles, then yes—it's worth it.


upvote icon
Upvote0
Comment
0
Share