Note: The job is a remote job and is open to candidates in USA. Metasys Technologies is seeking a Geospatial Data Scientist to transform complex spatial data into actionable insights. The role involves working across the geospatial pipeline, from data ingestion to visualization, and collaborating with engineering and product teams to embed spatial intelligence into their platform.
Responsibilities
- 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
Skills
- 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
- 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, Deck.gl)
- 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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