James_

Hello all! I have been putting a lot of thought into going back to school and getting a PhD, and wanted to get some advice on my strength of profile. My path might be a little atypical, perhaps backwards, but I do wonder how it would be perceived. I finished a bachelor's degree in pure math in 2019, then went on to do a non-thesis master's in Statistics and machine learning, which I completed two years ago. So, for the past two years I've been working at a large biotech company as a Data Scientist. Most of my time at this company has been with global research, where my work has been focused on model experimentation and pre-patent creation for various improvements to specific instruments. Does this atypical path have any positive/negative effects on my future application? I know that my Master's would not be transferable, but does it strengthen my profile? I've compiled a list of schools below. Are any in reach? Below is my profile: Undergrad Institution: Top 100 State School (Top 50 in Math) Major: Mathematics GPA: 3.84 (Major 3.94) Type of Student: Domestic White Male Graduate Institution: Same as undergraduate institution Focus: Statistics and Machine Learning GPA: 4.0 Research Experience: Math REU Several Machine Learning Projects Statistical Consultant for Interdisciplinary Statistics Lab helping other graduate students Over a year of experience working in Global Research for a large biotech company Awards/Honor/Recognition: Dean's List six semesters Math Honor Society Phi Beta Kappa Activities/Jobs: Was a TA for upper division math stats course Data analyst for astrophysics researcher Data scientist for 2+ years at biotech company Statistical consultant for a lab at school Grades: Undergrad Courses: Calc I/II/III A's, Linear Algebra A, Discrete Math A, ODE A, Introduction to Complex Analysis A Upper Division: Analysis I and II A, Abstract Algebra A, Probability Theory A, Differential Geometry of Curves and Surfaces A, Into to Data Science A Graduate Courses: Topology A-, Algebraic Topology A, Modern Algebra A, Coding and Cryptography A, Design and Analysis of Algorithms A, Statistical Methods and Applications I/II A, Mathematical Statistics A, Machine Learning A, Neural Networks and Deep Learning A, Markov Processes A, Statistical Learning A, Applied Deep Learning A, Statistical Collaboration A, Computational Bayesian statistics A LOR: It has been two years since graduate school so I'm a little worried about who I should ask. I can ask my boss (principal research engineer), but should a LOR come from a professor? There is a teaching professor that would write me a strong letter. Any thoughts or suggestions? GRE: I took this in 2019. I would have to take it again. V:154 Q: 158, W:4.0 Current Schools I'm interested in: Columbia, Harvard, Duke, Washington, UCLA, UC Irvine, University of Florida, CSU, UC Santa Cruz, UC Davis