Daniel is part of the quantitative research team which focuses on the collection, cleansing and synthesizing of Principia’s information. Daniel’s primary responsibilities include the development and improvement of algorithms for existing and developing models. In addition, Daniel supports overall research efforts through the analysis and interpretation of results in order to create and improve Principia’s data products.
Prior to joining Principia, Daniel worked for The Home Depot where he was responsible for creating product flow forecasts for the distribution network, creating linear programs to optimize volume for event season, and projecting labor requirements. Daniel has experience with Python, SQL, and Tableau.
Daniel earned a BS in Industrial Engineering from Georgia Institute of Technology.