Jaded Salaryman

Hi everyone, I'm preparing to apply to MS programs in stats or applied math next year (2022-2023). Undergrad: Top 100 undergrad private (US News) Major(s): Economics & Political Science GPA: 3.899 Background: International Male Asian Courses taken: Undergrad class: Calculus I-II, Intro Stats, Econometrics, Game Theory, Intro Programming for Science and Engineering Grades: all A Taken at my alma mater Linear Algebra and Real Analysis I Grade: waiting (at least B+, expecting A- or A) Taken at Harvard Extension (Math E-23a) while working full time Course is an integrated, proof-based treatment of linear algebra, multivariate and elementary real analysis (but not as rigorous as Harvard Math 25 sequence) Textbooks: Ross (for analysis) and Hubbard (for linear algebra & multivariate calculus) Courses planned: Linear Algebra and Real Analysis II (Math E-23b) GRE: 163Q, 164V, 4.5W (taken in December 2017, may have to retake to boost Q) Programs Applying: All MS. Some offer both Math and Stats MS (such as Wake Forest) Stats: Kentucky, Ohio State, UGA, Idaho, Colorado State Math: Alaska Fairbanks, Arizona, Bowling Green, Boise State, Wake Forest, South Dakota State, UMass Amherst Research Experience: None. Other Experience: Industry experience (working full-time since 2018) for a big e-commerce firm in Asia. Department: production support, now moving into business intelligence Some MOOC certificates: Andrew Ng's ML course on Coursera, WorldQuant University Applied Data Science Python, R, SQL Letters of Recommendation: mostly from undergrad econ professors Need your advice In addition to Linear Algebra and Real Analysis II above, I can only take at most 2 additional courses before application deadlines. What other courses should I take? My options are limited because I am outside the US and thus can only take online courses at Harvard Extension or UIUC NetMath. I'm deciding between: Abstract Algebra: Most MS in Math programs require this, but if I apply to MS in Statistics, this seems unnecessary Differential Equations: a math professor at my alma mater recommends this over abstract algebra if I cannot take both Probability Theory: I don't want to take this course since it is CAS-ILE based and has no lectures. It also doesn't seem to involve proofs. Is this class a must if I apply to stats MS programs? Intro Theoretical Computer Science (cross-listed as Harvard CS 121): the course involves writing proof so I think it may send a good signal Stochastic Methods for Data Analysis, Inference, and Optimization (cross-listed as Harvard APMTH 207): seems very computational and little theory Is my lack of research experience and LOR from stats/math professors a big problem? Do I have a good chance of getting TAships from these MS programs? Is my profile strong enough for unranked/low-tier stats PhD programs? My goal is to work in industry after graduation, so prestige is not an issue Many thanks!