At least 8 years of commercial experience as a Data Scientist or Machine Learning Engineer. Advanced scientific Python experience, including libraries like numpy, scipy, scikit-learn, pandas. Experience with geospatial or satellite data, and tools such as gdal, rasterio, shapely, fiona, geopandas, QGIS. Experience with deep learning algorithms, particularly in geospatial contexts, using tools like pytorch and tensorflow. Experience in leading small teams organized around projects or initiatives. Passion for climate issues. Enjoy working in a remote-first, fast-paced environment.