2019 Stat/Applied-Math Profile Eval & Advice

[galois]

Undergrad Institution: Small Liberal Arts College, Good but not well known school
Major: Mathematics

Concentration: Scientific Computing
GPA: 3.91

Graduated: 2013

Awards: summa cum laude, Phi Beta Kappa, Pi Mu Epsilon National Mathematics Honor Society, a number of college-specific prizes and scholarhips, JMM presentation prize

Type of Student: Domestic Mixed-Race Male

Relevant Courses:  Calculus I-III (A), Intro Statistics (A), Random Structures (B+), Foundations (A), Linear Algebra I-II (A), Abstract Algebra I-II (A), Number Theory Seminar (A), Mathematical Logic Seminar (A), Complex Functions (A), Real Analysis I (A), Euclidean & Non-Euclidean Geometry (A), Intro to Programming (A), Data Structures & Program Design (A), Complex Systems in Scientific Computing (A), Scientific Computing Seminar in Parallel Computing (A), Independent Study in Computational Algebraic Coding Theory (A)

 

GRE: (taking 8/11 for the first time)

GRE Subject Math: (taking 9/15 for the first time)

(Note: I'm cramming now, but given the time since undergrad, this subject score will likely be horrendous and I'll only send it if required)

 

Programs Applying:  Math/Applied-Math/Statistics MS/PhD (very undecided!). Probably unwilling to pay for MS, so ideally PhD.

 

Research Experience: 

- REU in combinatorial mathematics: presented at JMM, won poster presentation award, resulted in publication

- REU in gravitational physics: worked in a lab in Paris doing some experiments and analysis on a table top simulator for LISA mission.

 

Teaching Experience:

- Lead tutor for Calculus I-III for a few years, also helped in class with Maple syntax and stuff.

- Tutored an autistic client over a summer and increased his placement exam scores so that he could attend the local community college program.

 

Recommendation Letters: although its been 5 years, I made a great impression on my profs, and they were very happy to hear that I've finally decided to go back to school. I think these letters will be very strong.

 

Coding Experience: I've been in software development for over 4 years now. Standard web technologies, passable Linux sys-admin skills, experience in PHP, Javascript, Bash, etc., and more recently functional programming in Haskell. Did some C, C++, Maple, Mathematica, Matlab back in college as well.

 

Research Interests: not sure. Simultaneously interested in CS - programming language theory, Math - general applied math, also lately considering Stat with the goal of moving towards data science.

 

I'd love to solicit some advice. I do enjoy software development, but I'm not sure it will entertain me for an entire career. I've realized that I need to go back to school, if only because I've always wanted to study more math. My academic interests are in pure math, but I don't think I want to be in academia. Based on my latest foray into FP, I do think I would enjoy PLT, but I'm not sure I would enjoy general Computer Science, let alone 5-6 years of it. Furthermore, in the end I'd be looking for a research position in PLT and that would be very competitive.

 

So, I started to look at more general applied math. I figure I have mathematical talent that I should be using to help the world (which IMO has plenty of software devs), so I should study some applied math that could be used in more general situations, perhaps climatology research or helping elect sane politicians, etc. In balancing enjoyment of the degree and the career prospects afterwards (I've come to appreciate a higher-ish salary and remote work), lately I've been considering Statistics and moving into Data Science. My current background would probably complement that career path well.

 

Can anyone offer me advice? Specifically, what do you think about the degrees/careers I'm considering? Which schools do you think match my application profile? Should I be worried about having a 5 year break in studies? Given that I'd only be studying statistics as a means toward an industry career, and how I stayed away from stats in undergrad, how can I make my application look good for a PhD?

 

Schools of Interest:

University of Washington: Statistics/Applied-Math PhD

UT Austin: Statistics PhD

Duke: Applied-Math/Statistics - PhD

UNC Chapel Hill: Statistics/Operations Research - PhD

UC San Diego: Math (specialization in Stat) - PhD

UC Santa Barbara: Statistics & Applied Probability - PhD

UC Santa Cruz: Applied Math & Statistics - PhD

UC Irvine: Statistics PhD

U Hawaii Manoa: Math Phd

College of Charleston: Math/Statistics - MS

 

If you can't tell, location is a big deal for me. Fiance is unwilling to live anywhere cold, and I also love to surf, hence a lot of west coast schools. I'm local to Charleston, so if I don't get in anywhere, I'll probably do an MS there. Any suggestions on what I should add/remove to this list? Are any way out of reach for me, and are there any that I haven't thought of?

Edited August 2, 2018 by galois

[cyclooxygenase]

Not quite what you were looking for, but for climatology, you could also look at Atmospheric Sciences programs instead.  I'm given to understand most math-heavy students in such programs go more into dynamics than climate research, but regardless -- if you wanted to look at those, off the top of my head good programs would be Colorado State, Oklahoma, Washington (Seattle), Wisconsin (although less so these days), MIT (ditto?), and so on.  If you're really interested in that there are better sources than me, of course -- I'm just working off of my mom's time in climatology.

[galois]

I thought I'd be able to keep editing my original post as profile came to be, but I guess there's a time limit.

Undergrad Institution: Top 30 Liberal Arts College

GRE Raw: V 167 - Q 168

Felt like I earned at least a 4 on writing as well. Is that good enough for top programs? Can't decide if it's worth taking again.

I basically just want a solid program in a nice setting (read: surf available) where the living stipend is actually liveable. I'm starting to think most of the UC school stipends are simply not enough to avoid debt.

Edited August 11, 2018 by galois