6 of 6 GeoPandas Jobs in the UK excluding London

applied machine-learning experience, including time spent in an industry, product, or startup setting i.e. shipping models. Expertise in geospatial Python tooling: rasterio, xarray, geopandas, GDAL, and the STAC ecosystem. Hands-on experience training, evaluating, and debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision ...

applied machine-learning experience, including time spent in an industry, product, or startup setting i.e. shipping models. Expertise in geospatial Python tooling: rasterio, xarray, geopandas, GDAL, and the STAC ecosystem. Hands-on experience training, evaluating, and debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision ...

applied machine-learning experience, including time spent in an industry, product, or startup setting i.e. shipping models. Expertise in geospatial Python tooling: rasterio, xarray, geopandas, GDAL, and the STAC ecosystem. Hands-on experience training, evaluating, and debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision ...

applied machine-learning experience, including time spent in an industry, product, or startup setting i.e. shipping models. Expertise in geospatial Python tooling: rasterio, xarray, geopandas, GDAL, and the STAC ecosystem. Hands-on experience training, evaluating, and debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision ...

applied machine-learning experience, including time spent in an industry, product, or startup setting i.e. shipping models. Expertise in geospatial Python tooling: rasterio, xarray, geopandas, GDAL, and the STAC ecosystem. Hands-on experience training, evaluating, and debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision ...

Desirable Skills Experience with geospatial technologies and concepts, including: Spatial databases (e.g., PostGIS, BigQuery, DuckDB, Google Earth Engine) Geospatial libraries (e.g., GDAL/OGR, GeoPandas, Proj4, Gmaps, Leaflet, Leafmap,rasterio, STAC) Geospatial data formats (ESRI shapefiles, geojson, geotiff, zarr, geoparquet Familiarity with data science libraries like pandas. Geopandas, xarray ...