Microeconomic Surveys Section (Division of Research & Statistics) • Develops code for cleaning large data sets and executing economic models, conducts literature reviews, maintains technical documentation, and prepares publication and conference materials to help support research in topics such as racial wealth inequality, determinants of health, wealth measurement, gentrification, and survey technique. • Conducts research on the behavioral effects of pre-paid financial incentives on response rates, interviewer burden, and data quality for the Survey of Consumer Finances (SCF) as co-author to help inform future SCF field interview planning. • Managed updates to Stata and SAS programs to update analyses through multiple imputation rounds, developed code for benchmarking SCF data with other data sets, and edited verbatim responses to questions about demographics and financial habits to help improve data quality in the 2022 SCF. • Ran analyses using SCF data on various areas of household finance such as debt burden, non-wage income, retirement assets, housing wealth, intergenerational mobility, and pandemic experiences to help prepare official SCF reports and presentations. • Initiated, wrote, and presented new training memos for understanding the SCF production cycle and how to use the data to help improve onboarding and SCF user experiences. • Contributes to various TA roles for Howard University's Data Analysis in R course, helps host events for women in economics, and participates in various college outreach programs to support the Board's efforts towards increasing the economics pipeline.

• Cleaned Census data, created graphs and tables, and ran OLS regressions using Stata to support academic research on jails. • Cleaned administrative data, ran 2SLS regressions, conducted balance tests, and reviewed the literature on diversity in economics to help conduct a program evaluation. I am co-authoring the paper for the program evaluation project.

• Held weekly office hours to answer questions, help with exam preparation, and provide guidance for solving homework problems for up to 10 students at the same time.• Graded weekly problem sets and hosted monthly exam review sessions for introductory and intermediate level classes.

• Collaborated with a team to clean and analyze large survey data sets and create wealth indices based on ownership of durable goods and housing conditions to examine economic development.• Analyzed administrative and survey data, ran OLS regressions, and conducted literature reviews to evaluate the social effects of outdoor learning and explore its implications for gender gaps in STEM.

One of 20 students selected out of 1,300+ applicants to participate in the summer session hosted by Pathways to Research and Doctoral Careers (PREDOC). Awarded a full scholarship to enroll in the social science analytics course taught through UChicago Booth. • Attended weekly professional development seminars, coding labs, and lectures on quantitative research. • Cleaned IRI data on grocery store purchases using Stata to calculate the price elasticity of demand for grocery store coffee products in Illinois.

• Conducted a review of economics literature and reports from government agencies and reviewed calculations for a greedy algorithm and competition model to help revise an expert report for a litigation case.• Formatted tables using Excel, reviewed report citations, and compiled deposition preparation materials to help prepare for a litigation case.• Cleaned data on Python and Excel for a mergers and acquisition case while assisting colleagues in learning Stata under tight deadlines.