I very recently decided that I wanna get a PhD in stats - because of that, I have some fundamental lack of courses that I feel are required by most stats phd programs. Just wondering which schools I should target and what my chances look like?
Undergraduate Institution: Top 20 State school
Major: Math and CS (Joint)
Statistics/ML Courses: Mathematical Statistics I/II (A), Probability (no measure theory) (A), Stochastic Processes I/II (A), Machine learning (Graduate) (A), Data Science (A), Pattern recognition (A)
Math Courses: Calc I-III (A), Linear Algebra (lower division) (A+), ODE (lower division) (A+), Abstract Algebra I/II/III (A+), Convex optimization (graduate) (B+), Combinatorics (B+), Intro to proofs class (A), Numerical Analysis (A+)
MISC: Data Structure and Algorithms (A), Advanced algorithms (A), Theory of computation (A), Recommender systems and data mining (A+), Game theory (A-)
Note: I'm planning on taking a real analysis course from UIUC via https://netmath.illinois.edu before applying.
Another fact I thought might be worth mentioning - I'm graduating in 3 years.
GRE: 168; 164
Awards: Phi Beta Kappa, other misc. Academic / Research awards (2)
Research Experience: Worked on mathematical neuroscience research and currently two papers (second author) under review - not much stats involved at all.
Recs: Very strong from one math/cs professor and from my research PI.
Work experience: Data science / ML internships at two fortune 100 companies. Starting full time job at one after college.
I was planning on applying to:
Carnegie Mellon University
University of Chicago
John Hopkins University
New York University