Which MS program should I take?

Background: I am currently an SWE at Oracle India(1 year of experience), I wish to work for trading firms in the future in the US or Europe. I have done my undergraduate in Engineering, but I don't have a good GPA(7.9/10 or 3.4/4.0). I have good experience in Machine Learning and have good projects in it. Also, I have good work experience, I am also a Google Summer Of Code Mentor. I have a good GRE Score(169 Q, 160V) and good IELTS(111). Should I also take the GMAT?
I found these programs
  1. NYU MS in Math
  2. Imperial MSc in Applied Mathematics
  3. Imperial MSc in Mathematics and Finance
  4. Georgia Tech MS in Mathematics
  5. Georgia Tech MS in Quantitative and Computational Finance
  6. University of Washington MS in Applied Mathematics
  7. University of Washington MS in Applied Mathematics and Computational Mathematics
  8. University of Washington MS in Computational Finance
  9. Carnegie Mellon Master of Science in Computational Finance
  10. ETH Zurich Master Quantitative Finance
  11. University of Oxford MSc in Mathematics and Computational Finance
  12. King's College London MSc in Computational Finance
  13. Rochester Institute of Technology Computational Finance
  14. University of Edinburgh Computational and Mathematical Finance
  15. Stanford Master of Science in Financial Mathematics
  16. Purdue Computational Finance Masters
  17. University of Cambridge Masters in Mathematics
  18. University of Cambridge Masters in Applied Mathematics
What should I do to enhance my profile? Like research internship in maths, doing relevant courses on Coursera, or doing projects regarding finance?
I also found some online master's programs in Mathematics like University of Washington's online MS in Computational Finance, and CQF(certificate). Should I take any one of these to enhance my profile?

PS: I am not so sure about the pure Finance courses, if I should consider them too, please let me know.