Considering a Master’s in Data Science abroad?
Based on what I’ve seen mentoring applicants at SG Masters Pathways, this is something that you should know!
Top Global Universities
US: MIT, Carnegie Mellon University, UC Berkeley, Harvard University, Yale University, NYU, University of Washington, Georgia Tech
UK: University of Oxford, Imperial College London, UCL
Singapore: National University of Singapore, Nanyang Technological University
Switzerland: ETH Zurich, EPFL
Canada: University of Toronto, University of British Columbia, McGill
Germany: Technical University of Munich (TUM)
Netherlands: Delft University of Technology (TU Delft)
Australia: University of Melbourne, University of Technology Sydney (UTS Sydney), Monash University
What these programs expect from you
(1) A strong GPA (often evaluated internationally via WES or equivalent)
(2) Well-crafted essays + 3 recommendation letters
(3) Many programs are now GRE optional, which opens doors if you show strong academic readiness in other ways
(4) TOEFL/IELTS mandatory: Aim for 7.5+ overall and 7+ in each band to be competitive
(5) You don’t always need formal work experience, but you do need to demonstrate academic/technical readiness: extra coursework, relevant internships, projects, and strong quantitative skills
Application Timeline & Deadlines
· Most deadlines fall around January - February
· Duration: 1–2 years (depending on country and full-time vs part-time)
· Tuition: Roughly US $45,000 – US $90,000+ (varies greatly by country & university)
Career & Salary Outcomes post Masters
(1) The median annual wage for data scientists is US $112,590
(2) On job-boards like Indeed the average base salary for a Data Scientist in the U.S. is about US $128,965/year
(3) For entry-level data scientists (first year out) the median salary reported is around US $113,792/year
So yes, the investment is significant, but the return is there if you pick the right program and position yourself well
So, if you’re targeting a top international master’s in Data Science, it’s not enough to just apply. You need to build a strategic profile, and here’s what that means:
(1) Choose your university & program intelligently, align it with your strengths and career goals
(2) Start early on essays: show why-data science matters to you and what you’ll contribute
(3) Build a technical portfolio (coding projects, internships) - this demonstrates you’re ready
(4) Work on English test prep early - those 7s in each band matter
If you’d like help short-listing 5-10 data science programs that match your profile and building the full application roadmap (essays, résumé, testing strategy) - I’m ready when you are.
Book a consultation call here
Join our WhatsApp community
