Experience
Industry Experience
Cisco
Machine Learning Research Engineer
January 2023 - Present
Morgan Stanley
Quantitative Summer Analyst
May 2022 - August 2022
- Utilized Bayesian vector autoregression with historical macroeconomic data to forecast quarterly Consumer Price Index values for Poland, allowing for automatic quarterly prediction and reducing prediction time by 40%
- Forecasted customer stock prices based on supplier environmental, social, and governance features in supply chain relationship data leading to a 7% increase in model accuracy
Morgan Stanley
Office of COO: Data & Analytics Summer Analyst
May 2021 - August 2021
- Used blockchain and market data to cluster cryptocurrencies and build time-series models for short-term (one week) cryptocurrency price forecasting, increasing prediction accuracy by 13%
- Improved model prediction accuracy by ~10% for rival companies’ stock prices by identifying alternative data sources for prediction (e.g. patent data)
NextEra Energy
Data Science Intern
May 2020 - August 2020
- Built unsupervised models utilizing UMAP, t-SNE, DBSCAN, K-means, and K-medoids to cluster customer profiles using big data with both numerical and categorical features leading to a 60% customer ad engagement increase
- Built NLP and geolocation algorithms to match customer addresses, lowering outage response dispatch times by ~20%
- Converted IBM COBOL data to CSV and decrypted EBCDIC in Python
Research Experience
Machine Learning Department, Carnegie Mellon University
Research Assistant
November 2021 - December 2022
- Researched the impact of various ML pipeline design choices that amplify or remedy bias and fairness on downstream inequities in college admissions, measured through notions of predictive performance and predictive disparity
- Built a prototype testbed that displays the effects on bias from interactions between the construct and observed space
Department of Statistics and Data Science, Carnegie Mellon University
Research Assistant
August 2020 - December 2021
- Developed cross-state indicators of differing levels in prison quality using data from Pennsylvania Prison Society, Correctional Association of New York, and John Howard Association of Illinois to develop cross-state indicators of differing levels in prison quality
Behavioral Health Research Laboratory, Carnegie Mellon University
Research Assistant
July 2019 – December 2019
- Federally funded research that models social and biological factors in real-world contexts under conditions of alcohol use
- Analyzed various data sets using SPSS from participants, helped run clinical trials, and led several lab meetings