Jamey Smith

Jamey Smith is a highly skilled and impact-driven data scientist with a strong background in agriculture, environmental studies, and biogeography. With a Master of Science in International Agricultural Development from the University of California, Davis, he has gained extensive experience in analyzing geospatial data, including satellite imagery and other earth observation data, to develop and implement machine learning and deep learning algorithms.

Over the years, Jamey has contributed to various organizations, including Ramboll, where he currently works as a data scientist, Fraym, Development Seed, Biofuel TechSelect under Elsevier, and Inventure Renewables, Inc. He has also worked as a graduate student researcher at the Biogeography Lab and Horticulture Innovation Lab at the University of California, Davis. His passion for leveraging modern data science tools to better characterize landscape-level dynamics, particularly in agricultural systems, has been a recurring theme throughout his career.

Jamey's expertise and skills include spatial analysis, inferential and predictive statistical models, machine learning, and deep learning algorithms. He also has experience in intellectual property management, content management, and project coordination. With his perpetual curiosity and drive to have an impact, Jamey is a valuable asset to any team focused on data science and agricultural systems.