Applying to Data Science Masters with a weak GPA

[JTTCOTE]

Hello all! Happy Holidays!

Although I have a bad GPA, I feel that the other factors of my application are far better than my GPA would suggest. I'm wondering what sorts of Masters in Data Science programs I would stand a chance at.

How much can all the other aspects of the application make up for low GPA? Right now my plan is to spray applications everywhere in hopes that one of the schools out there puts less weight on GPA, which is not a great plan. I would hugely appreciate any insight in programs to apply to - I know what the top tier schools are, but I'm very unlikely to make it into those. Ideally, I'm looking for programs with a heavier machine learning component.

 

 

 

Undergrad: Carnegie Mellon, Major in Statistics & Machine Learning, double major in Chinese, minor in CS

GPA: 3.1 (overall and major happen to be the same)

GRE: 167Q / 169 V / 5.0 A

No research/work experience

Internships:

Small (200-300 person) company where I solo built an ML model (conv. neural net) saving them 100k+ a year

Microsoft data science intern (NLP work, but no results in the time I was there)

Rec letters:

Alg&Data Structures professor - we talked often and I nailed the course, 92 vs a class avg of 76.

Stats professor - took a corporate capstone project, did good work with them and went to prof often for advice.

Microsoft boss who liked me & my work.

Edited December 28, 2019 by JTTCOTE
minor changes

[Stat Assistant Professor]

WIth a 3.1 from Carnegie Mellon and that GRE score, you would probably be able to get into most Data Science MS programs, outside of a few that are truly selective/competitive. Even then, I wouldn't rule out your chances. I would look at program websites and see what their basic requirements are. I assume most of them require a GPA that is 3.0 or higher, and if you meet that threshold, you probably stand an excellent chance.