Studied consumer finances using data from FRBNY Consumer Credit Panel, a dataset that contains retail loan data on 5% of all US borrowers, and performed empirical analysis (with economists Lily Liu and Michal Kowalik) - Wrote and maintained Stata code to automate large data pulls (>30GB) from SQL database and construct household-level dataset, merged in additional county and state-level data on demographics, employment, and pandemic information, and performed statistical analysis in Stata Analyzed the selling behavior of private equity managed CLOs in the syndicated loans market using Shared National Credit (SNC) dataset (with economists Michal Kowalik, Claire Labonne, Prof. Victoria Ivashina, and Angela Ma)- Ran regressions used to analyze the selling behavior of investors. Designed algorithm to match loans in SNC with Moody’s ratings data based on what time span ratings were in effect for, the default status of the firm, and rating levelInvestigated properties of spatial and quantile panel models (with economist Lina Lu)- Optimized estimation code for cluster computation, wrote Python code to automatically generate new iterations of code based on different data generating processesStudied credit card risk limit setting behavior of large banks (with economist Claire Labonne) - Used Python to develop a PDF table extraction tool that includes Optical Character Recognition capabilities. It can be used across different tables, automatically detects columns in edited pictures, and translates that into csv filesAnalyzed data from Fed facilities established to provide aid during the pandemic- Created US state-level maps to compare the geographic distribution of dollars and number of loans for the Paycheck Protection Program, also checked over existing code in QA process. Developed dashboard to show distribution of loans purchased by the Fed’s Main Street Lending Facility in coordination with UI teams

As a back end developer:- Wrote and maintained Python code for Natural Language Processing (NLP) functionality in abusiness insights application, performed testing to improve the accuracy of NLP models- Researched topics and toolsets in AI, deep learning, and Natural Language Processing. Shared anddiscussed learning with team members- Built xQuery APIs to view and manage health insurance benefit plansAs a data analyst:- Researched methodology of CMS healthcare spending projections to create simple model ofhealthcare spending growth in the US- Compiled macroeconomic data and national health data, cleaned up data using Python’s SciPy,NumPy, and pandas packages, performed analysis on data in R- Periodically presented findings from data analysis to team in BostonAs a front end developer:- Built out web app using Angular Javascript framework- Reported tasks on a weekly and daily basis in an Agile team

- Entered and coded information from over 600 resumes to create dataset on the careers of inventors- Performed preliminary analysis on dataset to determine if there were any changes in patenting forinventors based on career decisions, presented results of analysis to research group- Researched incentives to recruit participants for survey about the SUCCEED summer workshop,collected and digitized responses to surveys, wrote about the research methods used- Wrote script in VBA to match census block data to addresses in Excel spreadsheet- Wrote scripts in Javascript to check status of building permit information in Google Sheets- Initiated contact with Pittsburgh business owners for interviews about capital investments and coded interviews with owners of class B and C office buildings

- Created and implemented scripts in visual basic to cross check palliative-hospice care transitions in a claims data set of 10,000+ data points- Wrote and tested xQuery functions to update xml tables in consumer database-Developed idea for an app encouraging exercise in grade schools as part of a company-wide competition with approx. 20 teams, presented in front of various managers- Managed project for one of three intern app development teams in which we developed an app promoting fitness for users- Directed deadlines, project goals, and tasks for members of 4 member team- Assembled a set of technical specifications for the development team to develop the app in Android Studio- Designed, created, and implemented a survey that was administered to a population of Optum employees on wellness attitudes and behaviors in order to design incentives and marketing strategies for app, received 90+ responses

- Wrote Python scripts to scrape data from websites and check accuracy of data collected- Designed a Stata program that downloaded and charted data from the St. Louis Federal Reserve- Checked tax logic and debugged programs for the Open Source Policy Center's tax calculator- Helped to implement a Structured VAR model and bootstrap confidence intervals in Matlab- Performed background research on a variety of economic topics and datasets to use for analysis- Compiled and charted data in Excel, programmed code for data cleanup and analysis in Stata- Assisted in registration and Q&A at public events and conferences hosted by AEI

- Helped library patrons locate and check out books and media on the fourth floor- Moved, labeled, and organized library materials

- Took and typed up minutes for CMU Student Senate- Edited and revised minutes for publication

- Took orders, greeted, and conversed with residents in a friendly and timely manner- Ensured smooth service as part of a team of restaurant staff