Louisville Metropolitan Area
During my career I have broadly focused on developing and deploying models for prediction and inference, creating new and improved statistical methodology, and providing explainable results out of data. I currently work on the growth team at Wealthfront, and before this I spent two years at BCG as part of BCG X, building and deploying machine learning and data science models for major grocery retailers, automotive manufactures, industrial goods companies, and private equity firms. I graduated with my Ph.D. in statistics, during which my research was primarily focused on high-dimensional inference within regression settings. My experience in graduate school also included work on natural language processing (NLP), bioinformatics, categorical data analysis, data mining, probability theory and statistics. During and prior to graduate school, I worked in data analytics and data science, with experience in A/B testing, regression analysis, and machine learning at e-commerce, mobile gaming, and insurance companies.
- Trained xgboost and CatBoost models to accurately forecast $4b+ in annual repair spend for major automotive manufacturer - Built end-to-end models and logic with Azure, PySpark and Databricks to deliver 50m+ personalized offers for grocery retailer - Engineered comprehensive data pipeline to process 1M+ orders and built new features for discount modeling engine - Developed optimization algorithm with OR-Tools to identify 1000 new locations for private equity client’s portfolio company - Conducted NLP analysis with pandas, numpy, and NLTK to find business expansion intent in 5000+ financial documents
- Wrote and deployed code across multiple computing environments to generate simulation results and for real world applications using R, GitHub, Julia, and Penn State's high-performance computing cluster - Conducted research on hypothesis testing procedures for linear regression coefficients in high-dimensional data - Developed of high-dimensional inference procedures and R code for regression in GLM, partial linear models, and linear hypothesis testing scenarios
- Created presentations and delivered lectures to 200+ students across multiple 15 week semester long courses for the Department of Statistics - Wrote dozens of unique homework assignments, quizzes, and exams for each class taught - Held office hours to provide additional instruction and answer student questions - Courses taught (instructor of record): -- STAT 415 (Introduction to Mathematical Statistics): Summer 2019 -- STAT 319 (Elementary Mathematical Statistics): Fall 2019, Spring 2020, Spring 2022
- Lead weekly lab sections and conducted guest lectures for courses at instructor request - Graded assignments, quizzes and exams - Held regular office hours to answer student questions about course material - Teaching assistant for the following Department of Statistics courses: STAT 200 (Elementary Statistics), STAT 318 (Elementary Probability), STAT 380 (Data Science Through Statistics), STAT 470W (Problem Solving and Communication in Applied Statistics)