I am currently researching grad schools for a masters in data science and am trying to build up my list to apply next year. I remember while applying to undergrad, we were encouraged to make lists with safeties, targets, and reaches based on our stats and admission rates. I am trying to do the same for grad school but am unable to find any concrete stats on admit rates.
Is this something that is not publicly available or am I perhaps looking in the wrong place?
How would you recommend I identify target and safety schools apart from checking GPA?
Unfortunately I am not aware of a master list of acceptance rates. Remember admissions rates vary by university and specific program, unlike undergrad where admission rates are usually calculated for the entire college or in some cases specific sub-colleges or majors. I think your best course of action is to look at 10-20 programs that interest you by reputation or through guides and then dive into those programs’ websites to get an idea of the qualifications they are looking for. Do you have an adviser at your undergrad college who can help in your selection?
I have a general grad school advisor but not one specific to data science. She had mentioned looking into admission rates to find targets and safeties.
Even for qualifications for certain programs, I’m only able to find GPA (and rarely GRE) as quantifiable metrics to compare against. The rest are more subjective and rankings tend to vary as well, so are program-specific admission rates available anywhere? I have not been able to find any in my university specific research.
Have you tried calling the programs directly to get threshold GRE’s? My daughter had an idea of which programs to apply to based on the advice of her employer and undergrad professors. She was able to figure out a target GRE from piecing together various sources. At least for her PhD program in Chemistry, it seemed GPA’s and GRE’s were only an initial screen and the statement of purpose and LoR’s were what were determinative. She also had 2 years of research experience and some co-authorships. Data science may be a completely different assessment.
Hmm ok, I will definitely try reaching out to the programs directly. I was just a little stuck on how to identify “target” and “safety” schools because GPA is just one benchmark, and I think only one school I’m applying to even requires a GRE so I felt that may not be entirely representative of the admissions process. Is there any other quantitative factor that you think could potentially help me decide which schools to place as safeties/targets?
It’s very imprecise in that it’s only limited to those who post and depends what info they provide, but gradcafe has an admission results page - you may get some idea of what kind of stats are successful or otherwise at some of the programs you are interested in.
Maybe an indirect way is to look at rankings (US News or others) and assume higher ranked ones are more difficult to get into. You can also look at size of programs and conclude more spots = better chances and triangulate that with rankings. Do you know anyone who has already gone through the process? They should have some insights.
Yes, that makes sense. Unfortunately, I don’t know anyone personally who has gone to a masters program for data science but I’ll keep asking around. Thank you for your advice!
Don’t just “ask around”. Start with your professors-- both in data science and any related fields- CS, Applied Math, etc.
And when you meet with them have a very well thought out “elevator pitch” on why you are interested in a Master’s degree. That will help them guide you to former students doing relevant work…