> Developed and deployed machine learning models for time series with mixed frequency data in Python to forecast industrial growth with financial/macroeconomic indicators of equity excess returns, manufacturing costs and labor market indicators.> Automated daily MLOps processes in Python for corporate debt data from Bloomberg, ICE, and Refinitiv, leveraging the data to analyze and forecast international corporate borrowing behavior and its impact on the global economy.> Applied… Show more > Developed and deployed machine learning models for time series with mixed frequency data in Python to forecast industrial growth with financial/macroeconomic indicators of equity excess returns, manufacturing costs and labor market indicators.> Automated daily MLOps processes in Python for corporate debt data from Bloomberg, ICE, and Refinitiv, leveraging the data to analyze and forecast international corporate borrowing behavior and its impact on the global economy.> Applied a VAR model with sign restrictions in Python to analyze daily equity market returns in the US, UK, Euro area, and Japan, decomposing returns into orthogonal shocks from inflation, hedging premiums, growth, and monetary news.> Provided special briefings to the Board of Governors on global financial conditions, international role of the US dollar, and measures of corporate distress abroad. > Constructed country- and region-level indexes of financial stress to monitor the effects of global macroeconomic shocks on a broad set of asset prices.> Investigated the spillover of China’s real estate bankruptcies & defaults into the US bond market.> Illustrated changes in global bond and equity and foreign exchange markets for the Spring 2022 Monetary Policy Report presented with Fed Chair Jerome Powell's testimony to the US Congress Show less

> Analyzed the impact of attorney processing delays on Social Security Disability Insurance (SSDI) benefit claims using a difference-in-differences model in R, leveraging data on disabled individuals' average earnings.> Automated web scraping of public county court hearing data using Python, Selenium, and BeautifulSoup to gather information on evictions and undergraduate student outcomes.> Developed police dispatch data model for US metro areas isolating domestic violence… Show more > Analyzed the impact of attorney processing delays on Social Security Disability Insurance (SSDI) benefit claims using a difference-in-differences model in R, leveraging data on disabled individuals' average earnings.> Automated web scraping of public county court hearing data using Python, Selenium, and BeautifulSoup to gather information on evictions and undergraduate student outcomes.> Developed police dispatch data model for US metro areas isolating domestic violence specific calls in R. Show less

Assisted in the instruction of Introductory Econometrics. > helped students recognize barriers and methods for identification> assisted students with the linear algebra and statistics used to derive estimators, bias, and variance and asymptotic behavior of estimators> taught students basic programming needed for analyzing empirical data

> Implemented end-to-end marketing research efforts from leading in-person customer focus groups, to synthesis of responses, to marketing strategy formulation, to statistical analysis of the performance of our marketing strategy.> Analyzed shipping data using Python to track late pickup and delivery trends from third-party providers, optimizing shipping expenses and identifying the most profitable contracts.> Developed real-time dashboards in Tableau to monitor excess… Show more > Implemented end-to-end marketing research efforts from leading in-person customer focus groups, to synthesis of responses, to marketing strategy formulation, to statistical analysis of the performance of our marketing strategy.> Analyzed shipping data using Python to track late pickup and delivery trends from third-party providers, optimizing shipping expenses and identifying the most profitable contracts.> Developed real-time dashboards in Tableau to monitor excess inventory, customer purchasing patterns, and the effectiveness of promotional sales and limited-time offers.> Optimized our company’s data management with the introduction of Snowflake unifying our multiple database management systems and adding efficiency to our Tableau reporting. Show less