Data Scientist

Data Scientist (Geospatial & Spatial Analytics) London (Hybrid - 3 days office) £75,000 - £85,000 + Equity + Benefits MNRecruit has been retained by a fast-growing climate-tech and spatial intelligence company based in London. They build cutting-edge platform solutions that analyze satellite earth observation data, climate risk models, and geospatial analytics for global financial institutions and energy developers. They are seeking a Data Scientist with deep expertise in spatial data science, machine learning, and geospatial software packages to join their core analytics team. Key Responsibilities: Spatial Data Science: Build and deploy machine learning models (random forests, CNNs, spatial regression) on large raster and vector datasets. Earth Observation Processing: Process, normalize, and analyze satellite imagery (Sentinel, Landsat, commercial SAR) for land cover classification and environmental monitoring. Geospatial Pipeline Engineering: Build scalable data processing pipelines in Python using Cloud-Optimized GeoTIFFs (COG), STAC APIs, Xarray, and Dask. Model Optimization: Optimize spatial algorithms for high-performance computing in cloud environments (AWS / GCP). Collaboration: Work closely with product managers, software engineers, and domain experts to integrate ML outputs into customer-facing web APIs. Key Requirements: MSc or PhD in Geospatial Data Science, Computer Science, Remote Sensing, Physics, Mathematics, or related quantitative discipline. 3+ years commercial experience as a Data Scientist focusing on geospatial datasets. Advanced Python skills: PyTorch/TensorFlow, GeoPandas, Rasterio, Xarray, Shapely, PySAL. Proven track record handling satellite remote sensing data (Sentinel-2, Landsat, SAR). Experience with cloud-native spatial formats (COG, Zarr, GeoParquet, Parquet). Strong background in statistical modeling, spatial statistics, and machine learning. What's on Offer: Competitive base salary (£75k - £85k). Meaningful equity options package. 3 days per week in a modern central London office, 2 days remote. Health insurance, learning budget, and high-spec workstation setup. Application: Apply via MNRecruit with your updated CV and GitHub / portfolio link if available.