MS Stats UCLA vs UW

[bistromathic]

Hi everyone,

I have to decide very soon between a masters in statistics at UCLA vs University of Washington. I'm in CA, so UCLA is cheaper because of in state tuition, and it seems to be shorter (possibility of finishing in one year, vs 2 years at UW). UW is stronger academically, and I would be able to better pursue my interest in machine learning there. I'm interested in working as a data scientist afterwards. Could anyone comment on the reputation of these masters programs, and what kinds of jobs graduates get afterwards? Or any other advice on this decision would be appreciated!

[Stat Assistant Professor]

How much debt would going to UW put you in? Is there no financial support from either program? If the amount of debt were similar, I would pick UW, but not if it means going into a *lot* more debt. Then I would just go to UCLA.

Edited April 18, 2014 by Applied Math to Stat

[cyprusprior]

I would recommend contacting UW and finding out whether you can get a position as a research assistant as a masters student. I think that there are many projects beyond just the stats department that might be seeking RAs to help with basic applied statistics that could provide some funding.

[BlueRobin]

Another factor to take into account is where you'd like to work after finishing your MS. For example, if you'd prefer to work in California, it will probably be easier to find a job there if you are in UCLA.

[bistromathic]

Thanks for the responses. The increased level of debt at UW is significant (~$30k more). I am interested in jobs in the bay area, so I'm not sure if UCLA has any advantage over UW there.

[wine in coffee cups]

I can comment a bit on UW's program. It's new as a formal master's program and the first group of seven students is just finishing this spring, so not a lot of outcomes to report on yet. Two of the students are moving on to statistics PhD programs (one staying at UW, other going to Yale). The remaining are job hunting, to my knowledge, mostly looking at data analyst positions, I think at least two have accepted job offers already in the Northwest. The current first year master's cohort is larger, 18 students, not sure what their goals are generally. Most are from China, though there are a few US citizens. Next year, even bigger I would guess? RA funding is unlikely to happen for master's students, as the overall TA/RA situation is already tight for the PhD students and they get priority. I think some are master's students are graders for undergrad classes, don't know of any first years who TA or RA, one of the second year students TA'd. So in terms of funding to offset the cost of the program, in practice this is pretty limited so far.

 

The coursework is theoretical and shares a lot of the requirements with the statistics and biostatistics PhDs. If you are thinking at all about going on to a PhD, it's definitely good preparation, the coursework is undeniably rigorous. The first year theory sequence and the second year methods sequence involve a lot of homework and are particularly time consuming. For the most part, the offerings are traditional statistics classes, which are interesting and challenging but not direct professional training. For machine learning offerings specifically, see here (note the theoretical emphasis). There are some electives that could be useful to someone interested in a data science career who wanted to get a portfolio started, such as the popular new "machine learning for big data" class which demands a lot of programming and a substantial final project. The required first year linear regression class and elective nonparametric regression class also usually have final projects and a poster/presentation, again, perhaps nice for portfolio building and interview fodder. I haven't heard too much about the required master's capstone class, but I think it involved some sitting in on consulting sessions and seemed more practical than most of the other coursework, may be somewhat useful for learning how to bridge the divide between real problem posed by a non-statistician and a solution grounded in statistical theory.

 

The department forwards on job postings it receives to students, seems like a few per week, emphasis on local employers but some things from all around the country, but doesn't maintain any kind of job database or resume service. You can go through general UW career advising of course, job fairs and whatnot. Not sure how that compares to whatever UCLA does for its students. The university has an overall very strong reputation in statistics and computer science, though, and I don't think it would be hard to get employers to take your training seriously coming out of UW. Unfortunately can't tell you if this is worth the premium over a shorter cheaper program at UCLA.

[tamy]

You can actually check its job placements here: http://www.stat.washington.edu/personnel/index.php?sort=year+desc&search=&field=name&discipline=A