Profile
Senior data science and modeling professional specializing in forecasting, time series analysis, and alternative and unstructured data. Combines hands-on statistical modeling and technical leadership with the development of reliable analytical pipelines and data products for economic and financial research. Author of R for Economic Research.
Areas of Expertise
Data: Time series · Alternative, Unstructured, and High-Frequency Data
Modeling: Econometrics · Machine Learning · State-Space Models · Bayesian Inference
Delivery: APIs · Data Apps · Automated Reports
Workflows: Data Pipelines · LLM Integration
Tech stack: R · Python · Shiny · Quarto · DuckDB · PostgreSQL · dbt · Git · Docker · Shell/CLI
Professional Experience
- Lead the Data Science and Modeling team within Macroeconomic Research, providing technical direction and overseeing the development of quantitative models and analytical products.
- Develop forecasting and nowcasting models for inflation and economic activity using alternative, high-frequency, and unstructured data.
- Design and implement models to estimate latent economic variables, including potential output and the NAIRU, at scale across dozens of countries.
- Build end-to-end analytical workflows that operationalize models and research, integrating LLM-assisted tools into the pipeline to process information, support analysis, and generate analytical outputs.
- Developed economic activity and inflation indicators using alternative and unstructured data, expanding the information available for macroeconomic analysis.
- Designed and implemented forecasting models for COVID-19 cases and vaccination coverage, developing modeling approaches for rapidly evolving processes with limited historical data.
- Developed forecasting models for revenues of publicly listed companies, combining economic and company-level data to support investment research.
- Built machine learning models using credit-market data to predict corporate bond prices.
- Conducted applied economic research and monitored regional economic activity using official and administrative data.
- Developed statistical indicators and analytical tools to measure economic conditions and support public-policy discussions.
- Produced reports and presented quantitative findings to technical and nontechnical audiences.
Education
M.S. in Economics, Universidade Federal Fluminense · 2017
B.S. in Economics, Universidade Federal Fluminense · 2013
Publication
Author of R for Economic Research, a practical guide to data workflows, statistical modeling, time series, and forecasting for applied research. The book has received more than 55,000 views from readers in over 50 countries.
Selected Presentations
Nowcasting When Predictors Keep Changing: Leveraging Cross-Sectional Information in High-Dimensional, High-Turnover Data — International Symposium on Forecasting · Montreal · 2026
Nowcasting Inflation in Brazil Using Web Data — International Symposium on Forecasting · Charlottesville · 2023
Real-Time Forecasting of COVID-19 Cases Across US Regions — International Symposium on Forecasting · Remote · 2020