CMU MCDS vs MSCS at Columbia, NYU or Stanford?

[pfish861]

I have got into 2 programs and am waiting on other two, but have to get back on admitted programs soon. My main aim is to do research to put me in a better position for PhD in ML (deep learning and/or probabilistic modeling) later on but also keep option open for a job in machine learning like data scientist, machine learning scientist or research engineer in case I do not get into a PhD with an advisor in my research area. Below are my thoughts on the pros and cons of each.

CMU MCDS: Great all around in terms of professors, research, courses and reputation. However, it is billed as a professional degree and so if I don’t get to do enough research with the right profs I would need to look for job and the kind of jobs available are mainly software engineer.

Columbia MSCS: There is a thesis option but very little clarity on how many students are actually able to move on to successful PhDs in future as unlike CMU they don’t post information on alumni. I could hardly find any masters students on faculty research group pages so not sure if they are accepted by Profs for research positions.

NYU MSCS: I have seen a few MS students here doing research with faculty but it’s the highest risk in terms of getting a job if PhD doesn’t work out as I’ve heard most of the people getting jobs in NYC banks which is not my top priority.

Stanford MSCS: I almost certainly would take Stanford over all these as I think it provides the best balance of both choices but here too I see it markets itself as more of a terminal degree so I am confused.

Kindly advise which one I should choose given my situation which has the maximum research potential.

Edited March 8, 2017 by pfish861