Dylan Rich
Geospatial Scientist
Machine Learning + Data Science + Geospatial Analysis
As a Geospatial Scientist Dylan uses his experience in machine learning, remote sensing, and geospatial technologies to develop scalable solutions to complex carbon accounting problems.
Background & Bio
Dylan has spent most of his career focused on creating real value for end-users and customers throughout a variety of roles and across several industries. To this end he has worked in roles spanning most parts of the customer journey: applied scientist, customer success engineer, solutions architect/engineer, pre-sales engineer and most recently machine learning engineer at Pachama.
Dylan brings a wealth of geospatial expertise with him to Carbon Direct. He has worked with dozens of remote sensing platforms and derived/modeled geospatial datasets. In previous roles he has scaled large geospatial data pipelines and models to serve analytics to customers. He has worked on applications and solutions for several industries including agriculture, energy, and climate.
Education
BS Mathematics
Seattle University