Advice needed on applying to Data Science programs

[L2norm]

Hi everyone, I'm currently an undergrad, math major (with a focus on stats) at a top 15 liberal arts college and will be applying to data science master's programs this year for fall 2021. Throughout my time at college, I have taken lots of statistics classes and classes like "Big Data and Machine Learning", "Math of Machine Learning" etc. so I've had a strong exposure to data science areas as well extensive training in programming languages like R and python in implementing machine learning techniques (like monte carlo simulations, bootstrapping, decision trees, random forest, clustering, SVM, little bit of ANN etc). I have 2 summers and 2 semesters of research experience in a computational biophysics lab. I also have an actuarial internship under my belt where I worked at the intersection of the actuarial science and data science departments at the company. 

The downside is that my GPA is not so great: 3.35. My grades in stats, machine learning and CS classes have all been A/A-'s and one or two B+'s. My grade in linear algebra and multivariable calculus are B and B- respectively. Is that going to hurt my chances a lot, or will the fact that I excelled in those stats and machine learning classes compensate for the bad grade in calculus and linear algebra? 

I am aiming for a GRE score of 170 in quantitative section and 165+ in the verbal section. I'm sure my recommendation letters and personal statement are all going to be stellar. Given all this information, do you think that my background is sufficient enough to make me a competitive candidate for data science programs? These are the schools whose DS programs I am considering applying to: Columbia, Harvard, Upenn, Georgetown, USC, USF, UVA, UChicago, NYU, Stanford. 

Am I being too ambitious?  Are there programs in other schools where I have higher chances of getting in that you would recommend?

ANY comments/insights would be HIGHLY appreciated. Thank you so much!

[DanielWarlock]

Your GPA is too low and you struggled with basic math stats class on undergraduate level. I would caution you applying to Chicago and Stanford.  Even if you are admitted, you will be having problems completing the course requirement. 

[L2norm]

5 hours ago, DanielWarlock said:

Your GPA is too low and you struggled with basic math stats class on undergraduate level. I would caution you applying to Chicago and Stanford.  Even if you are admitted, you will be having problems completing the course requirement. 

Does that mean that I have zero chances of getting in at any of the aforementioned schools?

[bayessays]

First off, the above response is very presumptuous about a lot of things.  Plenty of people get Bs in low undergraduate math courses and then go on to complete PhD coursework successfully, so I don't agree with Daniel at all.  These aren't the Stanford/Chicago PhD programs, so the coursework isn't that theoretical, and the OP goes to a top college with perfect test scores - I'm nearly 100% sure they would be able to make it through these programs successfully.

That being said, I think it is probably a stretch to be admitted to those programs, which are the 2 most prestigious and well-known, if you don't have some higher math classes with As.

I've been surprised how competitive many of the MS data science programs are getting.  Have you taken calculus-based probability and statistics and done well?  If so, I think you will get into schools like Georgetown, USF, UVA, USC, but I think the Ivies are pretty competitive now.  This is a pretty uninformed opinion though, as there isn't a ton of data on these new programs and they are growing in popularity/competitiveness.

[DanielWarlock]

11 minutes ago, bayessays said:

First off, the above response is very presumptuous about a lot of things.  Plenty of people get Bs in low undergraduate math courses and then go on to complete PhD coursework successfully, so I don't agree with Daniel at all.  These aren't the Stanford/Chicago PhD programs, so the coursework isn't that theoretical, and the OP goes to a top college with perfect test scores - I'm nearly 100% sure they would be able to make it through these programs successfully.

That being said, I think it is probably a stretch to be admitted to those programs, which are the 2 most prestigious and well-known, if you don't have some higher math classes with As.

I've been surprised how competitive many of the MS data science programs are getting.  Have you taken calculus-based probability and statistics and done well?  If so, I think you will get into schools like Georgetown, USF, UVA, USC, but I think the Ivies are pretty competitive now.  This is a pretty uninformed opinion though, as there isn't a ton of data on these new programs and they are growing in popularity/competitiveness.

The OP doesn't have perfect test score. It is only his/her hypothesis. Likely OP will get suboptimal GRE. OP's GPA is also very bad, to be blunt, for the top master programs. That said, OP has good working/research experience--if the letters are as good as OP claims, the chance is better. But I don't think Stanford is a possibility for OP since there are only 8 globally admitted. UChicago is a huge stretch also. I applied to both programs and was rejected and my stats then was much better than OP. 

Columbia is easier from what I heard as a "cash cow program" but I didn't apply. I interviewed with a few guys there at a bank during my old life. They appeared to be very strong quantitatively so OP may still fall short but I'm not certain.

@bayessays 

I have first-hand experience with PhD and master applications. And I will say master application is no less competitive than PhD at top venues. For example, Harvard data science master probably has lower admission rate (5%) than the PhD program (10%), although the focus certainly differ.

Edited February 28, 2020 by DanielWarlock

[BL250604]

13 minutes ago, DanielWarlock said:

I have first-hand experience with PhD and master applications. And I will say master application is no less competitive than PhD at top venues. For example, Harvard data science master probably has lower admission rate (5%) than the PhD program (10%), although the focus certainly differ.

I respectively disagree. I got into a handful of top masters programs (5/6) and only into 6/14 ph.d. programs. I'd be willing to argue that masters programs are far less competitive. All of my 6 M.S. applications were to top 15 schools, 3 of which were top top tier (Yale, NYU, Columbia, etc.)

[DanielWarlock]

10 minutes ago, BL250604 said:

I respectively disagree. I got into a handful of top masters programs (5/6) and only into 6/14 ph.d. programs. I'd be willing to argue that masters programs are far less competitive. All of my 6 M.S. applications were to top 15 schools, 3 of which were top top tier (Yale, NYU, Columbia, etc.)

Columbia, NYU, Yale are all not "top top tier". They are of medium to low tier in terms of competitiveness. In fact, Columbia master program admits like 500 students per year. PhD and masters have different focus. That may be why you struggle with PhD application more. 

Edited February 28, 2020 by DanielWarlock

[L2norm]

Does anyone else have any other comments? Please ?

[jelquiades]

Your grades may make it difficult to get admitted to many of the schools you listed, but the good news is that a lot of schools have data science programs nowadays. I suggest you click around a little on department websites (of different levels of prestige) and find out about where their graduates go and if it aligns with the job you want.

I was in your position about a year ago, not knowing which schools to look at outside of the big boys. It's difficult to suggest masters programs since there are so many of them. What I did to get started was basically choose schools at random on the usnews ranking and go from there.

[MathStat]

I personally do not think average grades in multivariable calculus and linear algebra are so dramatic. 

For what it is worth I got B+ in multi because I couldn't do the tricky double/triple integrals fast enough during the midterms. This did not affect my phd admissions but granted I had grad level math courses with As to make up for it. 

Linear for some is also a tricky course the first time you see it. If I hadn't struggled with it before in high school I would've also gotten a B in my first semester linear class. I would say it is perfectly understandable to mess up the math classes in your first year if you didn't have exposure before. 

" My grades in stats, machine learning and CS classes have all been A/A-'s and one or two B+'s. " <- that is very good. 

The nice thing I notice about the United States is the culture of "second chances". The postdoc who helped me immensely to develop beautiful undergrad research also messed up his linear/multi and other math classes in undergrad. He said he had mostly bad grades during his math BS at UW. He stayed for a masters to fix his background, then did very well in his math phd and was able to secure a postdoc at duke with one of the best probabilists in the world. There are tons of similar examples from stat, including a stat professor I had at duke who climbed her way up from not prestigious undergrad and masters to phd at UFlorida, then postdoc at CMU, then tenure track at Duke. There is hope @L2norm! Many established and strong researchers were able to not let their  "humble" beginnings define their future. The issue is that all that I know of are American citizens...so i can't really comment about internationals. 

The question is: since your gpa is rather low but your math/stat/cs course grades are pretty good since you only have 2 Bs, it means you messed up most of your humanities/social sciences classes. Do stat programs really care about this?

[umichmydrm]

34 minutes ago, MathStat said:

I personally do not think average grades in multivariable calculus and linear algebra are so dramatic. 

For what it is worth I got B+ in multi because I couldn't do the tricky double/triple integrals fast enough during the midterms. This did not affect my phd admissions but granted I had grad level math courses with As to make up for it. 

Linear for some is also a tricky course the first time you see it. If I hadn't struggled with it before in high school I would've also gotten a B in my first semester linear class. I would say it is perfectly understandable to mess up the math classes in your first year if you didn't have exposure before. 

" My grades in stats, machine learning and CS classes have all been A/A-'s and one or two B+'s. " <- that is very good. 

I have B on my Linear Algebra and Intro CS, and I have all A in other math classes, but I still find myself not competitive because of my 3.5 cumulative GPA(I have three Biology classes in B, one econ class in C, and a seminar class in C-). I believe the admission process would be extremely tough if you are an international student. 

Edited March 9, 2020 by umichmydrm

[MathStat]

I see, this may indeed be a sad reality for international students and so the solution may indeed be doing whatever masters you can get that has a strong researcher there to discover you and believe in you. 

[umichmydrm]

4 minutes ago, MathStat said:

I see, this may indeed be a sad reality for international students and so the solution may indeed be doing whatever masters you can get that has a strong researcher there to discover you and believe in you. 

Yeah, there are many international students with stunning GPA and GRE scores.