Sr. Data Scientist

Geospatial Data ScientistRemoteThis is a Remote role.Compensation: $80 - $88 per hourAbout The RoleOur client is seeking a Geospatial Data Scientist to transform complex spatial data into actionable insights and support product and business decision-making. In this role, you will work across the full geospatial data pipeline—from data ingestion and processing to analysis, modeling, and visualization—and collaborate closely with engineering and product teams to embed spatial intelligence into our platform. You will be responsible for developing and maintaining spatial data models, applying machine learning techniques to spatial problems, and creating compelling visualizations for diverse stakeholders. The ideal candidate thrives in a fully remote, asynchronous environment and brings a solid understanding of geospatial standards, coordinate reference systems, and data quality management.What You'll DoDesign and execute geospatial analyses to support product and business decision-makingBuild, validate, and maintain spatial data models and pipelinesQuery and manage geospatial datasets using PostgreSQL with PostGISWork with geospatial data formats including GeoJSON, Shapefile, GeoTIFF, WKT, and WKBDevelop machine learning models with spatial components (clustering, classification, interpolation, etc.)Create maps, dashboards, and visualizations to communicate findings to technical and non-technical stakeholdersCollaborate with backend engineers to integrate geospatial features into production systemsEvaluate and maintain geospatial data quality, coverage, and accuracyApply GIS tools (QGIS, ArcGIS, or equivalent) for spatial analysis and visualizationEnsure clear communication of geospatial insights in a remote, async environmentMaintain familiarity with geospatial standards, coordinate reference systems, and spatial indexingContribute to spatial data infrastructure and cloud-native geospatial workflows as neededWhat You Bring3–6 years of experience in data science, GIS, or a related fieldStrong proficiency in Python for geospatial data analysis and modeling (GeoPandas, Shapely, Fiona, Rasterio, or similar)Deep experience with PostgreSQL and PostGIS for spatial querying and data managementFamiliarity with geospatial standards and formats (GeoJSON, Shapefile, GeoTIFF, WMS/WFS, WKT, WKB, etc.)Experience with GIS tools such as QGIS, ArcGIS, or equivalentSolid understanding of coordinate reference systems (CRS), projections, and spatial indexingExperience applying machine learning techniques to spatial problemsAbility to communicate findings clearly in a fully remote, async environmentExperience with remote sensing or satellite imagery analysis (nice to have)Familiarity with cloud-native geospatial tools (PostGIS on AWS RDS, Google Earth Engine, etc.) (nice to have)Exposure to spatial data infrastructure (GeoServer, MapServer, Mapbox, Deck.gl) (nice to have)Experience with big geospatial data processing (Apache Sedona, H3, S2) (nice to have)Knowledge of Docker and containerized data workflows (nice to have)Familiarity with CI/CD and version control best practices (nice to have)