Staff Data Scientist, Wildfire

Leading the scientific foundation of the Fuel Detection Model, the full-time Staff Data Scientist, Wildfire will work remotely to estimate vegetation structure and wildfire risk using satellite and environmental data while collaborating with ML engineers and product teams. Key responsibilities Lead research on estimating vegetation structure, fuel conditions, and wildfire risk from satellite and environmental data Design validation methodologies and ground-truth strategies for model evaluation and uncertainty quantification Prototype ML modeling approaches and partner with engineers to implement them in production systems Required qualifications 8+ years of applied research or data science experience in wildfire science, fire ecology, forestry, or related fields Deep expertise in remote sensing and geospatial analysis, particularly with satellite imagery Strong statistical modeling and machine learning skills in Python, using tools like GeoPandas and scikit-learn Experience designing validation studies for environmental or geospatial models Proven ability to communicate complex scientific concepts to diverse audiences