Networks, Crowds, and Markets.

- Developed and implemented data analysis pipelines using SQL and Databricks, enabling the processing and analysis of large-scale healthcare datasets significantly faster than previous methods reducing day long processes to 2 minutes.- Synthesized complex healthcare data into actionable insights, directly influencing contract negotiations with stakeholders and informing the company's strategic analytical approaches.

- Engineered an R package to design the stress scenarios through a VARX, cutting the process time from 3 days to 2 hours. - Innovated bond yield curve modeling via Lasso regression into the Diebold-Li model, improving accuracy by 43%.- Developed a Shiny dashboard to visualize macroeconomic expectations and trends, facilitating internal stress test metric development.- Enhanced data processing workflows for network analysis, reducing the time requirement significantly and supporting bi-annual Financial Stability Reports. - Conducted joint research with BIS, producing econometric models to decode the Mexican credit market, including estimate elasticities, capital flow probabilities, and causal effects in natural experiments; findings were vital for policy recommendations. Engaged in geospatial analysis to visualize and interpret credit market dynamics.- Coauthored the paper A loan-level analysis of bank lending in Mexico, published in the Journal of Banking & Finance (2020), with Cantu, C., Lobato, R., Lopez, C., & Lopez-Gallo, F.