About me

Hi, I’m Daniel Silva-Inclan, and I’m open to new opportunities in data science and data engineering.

With 7+ years of experience as a researcher, data scientist, and data engineer, I specialize in turning complex challenges into tractable ML, AI, statistical, and economic problems and delivering analytics solutions that scale. These days, I’m at EY, where I help teams design, develop, and deploy enterprise-grade systems – from GenAI document-intelligence pipelines to cloud-native ETL workflows built on Databricks, Snowflake, and Azure.

My roots are in economic research. At the IMF and the Becker Friedman Institute at UChicago, I built optimization frameworks and synthetic data tools that made economic modeling faster, more reliable, and more reproducible.

My technical toolkit includes Python (pandas, sklearn, dbt, streamlit), R (tidyverse, shiny, leaflet, data.table), SQL, Docker, and cloud platforms like Azure (AI Foundry, MLflow, CosmoDB), Snowflake, and Databricks, with additional experience in Go, C/C++, and Julia. I’m always exploring new tools and frameworks to stay ahead.

Outside of work, you’ll find me tinkering with my home automation setup, self-hosting cloud services (home movies and my photography), experimenting with sous-vide and smoker recipes, or plotting my next strategic win in Age of Empires II: DE as I climb back to top 10%.