Role: Data Scientist With GIS
Location: 100% Remote
Duration: Six Month Contract to Hire
Top Skills'' Details
1. Python for data analysis and modeling (GeoPandas, Shapely, Fiona, Rasterio, or similar)
2. PostgreSQL & PostGIS for spatial querying & data management
3. Experience with GIS tools such as QGIS, ArcGIS, or equivalent
Job Description
We are looking for a Geospatial Data Scientist to turn complex spatial data into actionable insights. You will work across the full geospatial 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.
- Design and execute geospatial analyses to support product and business decision-making
- Build, validate, and maintain spatial data models and pipelines
- Query and manage geospatial datasets using **PostgreSQL** with **PostGIS**
- Work with geospatial data formats including GeoJSON, Shapefile, GeoTIFF, WKT, and WKB
- Develop machine learning models with a spatial component (clustering, classification, interpolation, etc.)
- Create maps, dashboards, and visualizations to communicate findings to technical and non-technical stakeholders
- Collaborate backend engineers to integrate geospatial features into production systems
- Evaluate and maintain geospatial data quality, coverage, and accuracy
- 3–6 years of experience in data science, GIS, or a related field
- Strong proficiency in **Python** for data analysis and modeling (GeoPandas, Shapely, Fiona, Rasterio, or similar)
- Deep experience with **PostgreSQL** and **PostGIS** for spatial querying and data management
- Familiarity with geospatial standards and formats (GeoJSON, Shapefile, GeoTIFF, WMS/WFS, etc.)
- Experience with GIS tools such as QGIS, ArcGIS, or equivalent
- Solid understanding of coordinate reference systems (CRS), projections, and spatial indexing
- Experience applying machine learning techniques to spatial problems
- Ability to communicate findings clearly in a fully remote, async environment
Additional Skills & Qualifications
Nice to Have
- Experience with remote sensing or satellite imagery analysis
- Familiarity with cloud-native geospatial tools (PostGIS on AWS RDS, Google Earth Engine, etc.)
- Exposure to spatial data infrastructure (GeoServer, MapServer, Mapbox
- Experience with big geospatial data processing (Apache Sedona, H3, S2)
- Knowledge of Docker and containerized data workflows
- Familiarity with CI/CD and version control best practices
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