Skip to main content

Code & Projects

A selection of data projects spanning environmental statistics, public policy analysis, and personal experiments in data visualization.


CEPALSTAT Environmental Data Pipeline

Automating regional environmental statistics for Latin America and the Caribbean

This system pulls environmental data from multiple international sources (FAO, OLADE, CAIT, CRED) and uploads it to CEPALSTAT, the region's central statistical database. It automates the entire pipeline for 90+ environmental indicators—from download and cleaning to quality validation and upload.

Built during my work at UN ECLAC to modernize how the region tracks environmental progress.

Skills: R, data pipelines, modular programming, data quality frameworks

View on GitHub →


Medicaid Enrollment Forecasts

Economic modeling to inform state budget decisions

Developed time series forecasts for Utah's Medicaid enrollment, incorporating historical trends alongside economic and demographic projections. These forecasts directly informed budget allocation decisions for the state's largest health program.

The models produced high-accuracy projections across multiple demographic segments, helping policymakers anticipate enrollment changes and ensure adequate funding.

Skills: R, time series forecasting, economic modeling, variable selection, mass model deployment

View on GitHub →


Reading Around the World

Visualizing literary exploration through data

A personal project that generates a colored world map based on my reading history. The pipeline cleans Goodreads exports, scrapes Wikipedia for author nationalities, and creates a visualization showing which countries' authors I've read—and how many books from each.

Skills: R, web scraping, spatial data visualization, API integration

View on GitHub →


Project KIDS

Following every education dollar to the student level

Integrated public education spending, demographics, and operational data to create the first comprehensive system for analyzing education investments at scale. The framework connects each dollar spent to individual student outcomes, enabling ROI-style assessment of educational programs.

Developed novel methodologies for linking disparate datasets and creating a unified analytical lens across school districts.

Skills: R, data integration pipelines, methodological development, fuzzy matching, scalable systems

View on GitHub →