Education
Massachusetts Institute of Technology, Bachelors of Science in Mathematics - June 2019
Coursework: Probability and Random Variables, Computational Statistics, Elements of Software Construction, Introduction to Algorithms, Machine Learning, Principles of Discrete Mathematics, Communicating with Data
Work Experience
Philadelphia Phillies
Machine Learning Engineer, Baseball R&D - March 2021 - Present
Quantitative Analyst, Baseball R&D - July 2019 - March 2021
Introduced a formalized experiment tracking system for the entire R&D department
Designed best practices and infrastructure for model registry and version management
Developed new statistics for player performance evaluation with machine learning models
Recommended in-game tactics through predictive modeling
Developed in-house tools to improve scout’s access to video information
Software Engineer Intern, Baseball R&D - May - September 2017
Compiled player evaluations and summaries for trades and draft
Improved employee access and understanding of databases through a React application that visualizes data structure and contents
Second Spectrum
Software Engineer Intern, Soccer Sports Performance - June - August 2018.
Designed new semantic markings within an active-learning framework
Implemented feature requests from independent research to production
Introduced new modeling techniques to improve team operations
Boston Bruins
Hockey Analytics Intern - January - June 2018.
Improved department’s understanding of statistics by conducting reliability studies
Automated pre-game reports through identification of key metrics from multiple data sources
Examined player projection and value evaluation through statistical models
Basis Technologies
Software Engineer Intern - June - August 2016
Refactored and maintained API bindings in 7 languages, including C#, Java, Python
Improved user access to the Rosette API through extensions for Google Docs, Excel, and RapidMiner
Skills
software development
Languages: Python, JavaScript + TypeScript, SQL, Java
Frameworks and Tools: React, Travis, test-driven development
Data Science
Languages: Python, R, SQL
Skills: Data visualization, supervised and unsupervised machine learning, descriptive and predictive modeling