Staff Geospatial Data Scientist

Location: London | Hybrid We're partnering with one of Europe's fastest-growing technology businesses to hire a Staff Geospatial Data Scientist into its Data team. The company operates a rapidly scaling, technology-led logistics network, moving millions of parcels through an increasingly complex last-mile operation. Geography sits at the heart of that network. Where demand occurs, how territories are designed, where capacity is positioned, how couriers move through cities and how the physical characteristics of an area affect delivery performance all have a direct impact on cost, speed and customer experience. The Role You'll work at the intersection of Geospatial Data Science, Machine Learning and real-world operations, using large-scale spatial datasets to understand and improve how the network operates. This is a senior individual contributor position with significant technical ownership. You'll work closely with Data Scientists, Operational Research Scientists, Engineers, Analysts and operational teams to turn complex geographic problems into production solutions. What You'll Do Develop geospatial models that improve how a large-scale last-mile network is designed and operated. Analyse millions of spatial and operational data points across parcels, couriers, routes, locations and delivery outcomes. Build models around travel time, accessibility, demand density, network coverage and geographic performance. Develop sophisticated spatial features and datasets that can be used across optimisation and machine-learning systems. Apply techniques such as spatial statistics, clustering, graph/network analysis and geospatial machine learning. Identify geographic patterns and constraints that influence delivery cost, capacity and service performance. Build scalable geospatial pipelines and tooling rather than relying on one-off analysis. Work closely with Operational Research and Engineering teams to integrate geospatial intelligence into production decision systems. Define technical standards and best practices for geospatial Data Science across the organisation. Mentor other Data Scientists and provide technical leadership on complex spatial problems. What We're Looking For Significant professional experience in Geospatial Data Science, Spatial Data Science or a closely related quantitative discipline. Expert-level Python and strong SQL. Deep understanding of geospatial concepts including coordinate systems, spatial joins, distance calculations, spatial indexing and geographic data structures. Strong experience with Python geospatial tooling such as GeoPandas, Shapely, PyProj, Rasterio, H3 or similar. Experience working with large-scale spatial datasets in a production technology environment. Strong understanding of spatial statistics, clustering, network/graph analysis or geospatial machine learning. Experience building production-quality Data Science systems rather than purely conducting research or GIS analysis. Strong software engineering fundamentals and experience collaborating closely with engineering teams. Ability to take ambiguous real-world problems, define the analytical approach and own solutions through to production. Comfortable operating as a senior technical IC and influencing technical direction across multiple teams. Particularly Relevant Backgrounds Experience within logistics, mobility, transportation, mapping, marketplaces, delivery networks or location intelligence would be highly relevant, although we're open to exceptional Geospatial Data Scientists from other technology environments. Experience with areas such as road networks, routing, travel-time modelling, geocoding, catchment analysis, territory design or spatial optimisation would also be particularly valuable.