Chau Nguyen

Instructional Associate for Dr. NaLette Brodnax for Advanced Modeling Techniques (PPOL 566) - the final course in the core data science sequence for the MS Data Science for Public Policy program. This course focuses on dimensionality reduction, unsupervised learning techniques, text analysis, and network analysis. The course builds off of the modeling concepts covered in Applied Statistical Learning (PPOL 565) by teaching students how to effectively analyze unstructured data. The course is taught in Python 3.

Guided research on neural networks’ limitations in object detection in paintings due to training images biases; collaborated with Dr. Toni-Lee Sangastiano (Department of Art and Art History - Georgetown University); presented findings in research showcase

Created prototypes of statistical model to identify renters in low-income areas using R, collaborated with cross-functional team of economists & engineers to put model into production

Developed log retrieval process in Python using boto3 to connect to AWS and extract log messages from over 5,200 cloud computing jobs, slashing over 10 minutes of manual search and match to view any single record Utilized clustering algorithm to discover text similarities in crash logs from over 1,000 failed cloud computing jobs; investigated clustered errors and pinpointed 8 gaps in R codebase where spatial interpolation process can fail Implemented workarounds to avoid crashes during feature selection process, eliminating 1/8 of identified issues Presented to management actionable insights to further improve core product in company-wide meeting

Managed internal database of Corporate Vulnerability Utility Index consisting of risk ratings for over 275,000 firms in 75 countries. Identified and addressed bugs causing CVU scripts (Stata & MATLAB) to crash, created detailed documentation for use as reference in the future. Contributed more than 200 descriptive charts and 60 tables published in over ten official IMF publications and five journal articles.

Main responsibilities include conducting deep dive analyses and statistical modeling on critical macroeconomic issues with a focus on Asia Pacific economies. Daily tasks include downloading economic data from multiple sources, cleaning and merging databases, writing programs to test time-series/panel data regression models in Stata, and R, and converting technical results to policy advice, and presenting to non-technical audience/senior leadership. Analyzed 140 millions USD in annual overseas transfers to Samoa; estimated that high legal compliance costs caused transaction fees to be 6% higher than sustainable development goals; findings highlighted in IMF report Conducted field research, interviewed country officials to solve significant data gaps in Tuvalu’s fishing sector which accounts for over 50% of GDP; authored first formal industry analysis published in 2018 IMF country report Developed strong verbal communication skills from relaying analysis results, forecasts, impact evaluations, and policy recommendations in non-technical terms to foreign government officials Created eight interactive Tableau dashboards to visualize and analyze data of over 70 countries in China's Belt and Road Initiative Managed four countries' macroeconomic databases, performed statistical checks for data consistency across all economic sectors.

Conducted research on a variety of topics including federal debt, taxes, immigration visas and food production. Created charts and Tableau dashboards to summarize findings.

Macroeconomics research

Public Economics research