Senior undergrad student. So I've had a slightly unconventional pathway through college. I came in just wanting to do chemistry and was pursuing a dual bachelors/masters in chemistry. However I realized I really didn't like doing lab work. I was minoring in Statistics starting the spring quarter of my sophomore year, and decided to bump it up to a major halfway through my junior year and drop the chemistry masters program. Since then I've been playing catch up with stats. I added Data Science as a minor just this last summer. Because of my chemistry classes, I didn't have the time to take any higher level math classes. I'll be taking a 300-level Math Optimization course next quarter, but I know programs like Real Analysis, which I don't have.
I will be going to work full time this summer as a mortgage analyst. It's not exactly what I wanted to do, but it's a great company and pays pretty well and I want to pay off my student loans before I go to grad school. So I'm thinking I'll work for 2-3 years then go to grad school. Ultimately I'd like to be a data scientist, financial quant, or something of the like. I've been thinking about a Stats PhD, but at this point I'm not sure I'd want to commit 5 years of my life when it's not totally needed. I'd ideally go to a good Stats MS program that is more theoretical, do a masters research thesis, and see if I enjoy the more technical/research side of Stats and from there go for a PhD (which hopefully I could transfer credit for). My full profile is below:
Student Type: Domestic White Male
Undergrad: Northwestern University
Major: Statistics and Chemistry
Minor: Data Science
GPA: 3.80
Math/Stats/CS classes: Honors Linear Algebra (A-), Honors Multivariable Calculus (A-), Introductory Statistics (A-), Mathematical Statistics I (A), Mathematical Statistics II (A), Mathematical Statistics III (P, Covid mandatory P/F), Financial Statistics (A-), Statistical Computing (P, Covid mandatory P/F), Multivariate Analysis (A), Regression Analysis (A), Survey Sampling (B), Introductory Econometrics (B), Introduction to Python I (A), Intro to Python II (A), Data Science I (A), Data Science II (A), Data Visualization (A), Hierarchical Linear Models (Not yet taken), Optimization (Not yet taken), Data Science III (Not yet taken).
GRE: Not yet taken, but I am a good test taker so I'm pretty sure I can get 90+ percentile on Quant
Research: 1) Summer REU at National Laboratory - more related to physics/programming in MATLAB/image analysis. Very little statistics. Credit on published paper.
2) very light research for statistics professor using PCA to study portfolios. I really haven't made much progress and it's not very theoretical. Nothing will be published by the time I graduate.
Letters of Recommendation: 1) Decent/strong from Stats professor I've taken two classes with and am doing light research with.
2) Decent/strong REU mentor (Physics Post Doc at National Lab)
3) Either data science professor who I'll have had for 4 courses (prof is not known at all) or potentially my future boss.
Applications: Would love to get into a top 10.
Although I won't be applying for another two or three years most likely, I want to set myself up as best as I can to get into a good program. Besides getting a really good GRE score (I'll probably take it this fall), what else can I do between now and then to improve my application? I was thinking I could continue doing research for the professor I work with now, or potentially reach out to other professors. I think with my job I'd be able to put in some decent hours doing stats research on the side. I don't know if that's worth it for Masters admissions though.
Any advice would be greatly appreciated! Thank you.
