Geospatial Data Scientist

• Review project requirements, client documentation, source datasets, reference geographies, and existing geospatial platform capabilities to define the geospatial implementation baseline.
• Assess geospatial data readiness, including raster datasets, vector layers, administrative boundaries, sub-national datasets, coordinate systems, spatial metadata, and known data quality constraints.
• Design and implement geospatial data preparation workflows, including geometry validation, coordinate reference system handling, reprojection, format normalization, clipping, joining, aggregation, simplification, enrichment, and spatial quality checks.
• Support raster and vector data processing requirements, including raster preparation, vector layer management, spatial indexing, tiling considerations, and preparation of datasets for downstream analytics, APIs, map services, or visualization layers.
• Participate in technical discussions with client stakeholders to clarify geospatial requirements, confirm assumptions, assess feasibility, explain limitations, and support acceptance of delivered outputs.

Scope of Work:

• Support the analysis, design, implementation, validation, and documentation of geospatial capabilities for the current project and future related initiatives.
• Implement or configure agreed geoprocessing functions, which may include buffering, proximity analysis, spatial aggregation, pattern analysis, classification, composite indexing, clipping, spatial joins, and sub-national processing.
• Support the preparation and publication of geospatial outputs through agreed mechanisms, such as GeoJSON, Shapefile, CSV with coordinates, GeoTIFF where applicable, map services, OGC-aligned service patterns, APIs, or export packages.
• Provide technical input to API and interoperability teams on geospatial service requirements, including OGC WMS, WFS, WCS, OGC API patterns, GeoJSON, metadata alignment, and geospatial API payload structures where applicable.
• Work with data engineering and data architecture teams to ensure geospatial datasets are correctly integrated into ingestion, transformation, validation, metadata, governance, and publication workflows.
• Support geospatial metadata, provenance, quality, and lineage requirements in coordination with data governance and catalogue teams.
• Define and execute geospatial validation activities, including sample maps, spatial accuracy checks, comparison against reference layers, export validation, format validation, and documentation of known limitations.
• Advise on geospatial performance considerations, including map loading, spatial query patterns, export size, raster processing complexity, tile generation, and service consumption patterns.
• Prepare clear technical documentation, configuration notes, supported format descriptions, workflow diagrams, validation evidence, operational considerations, and handover materials for technical teams.

Expected Deliverables:

• Geospatial requirements and scope clarification notes, including assumptions, dependencies, constraints, and open questions.
• Assessment of geospatial data readiness, covering available raster datasets, vector layers, boundary datasets, coordinate systems, spatial metadata, data quality issues, and preparation needs.
• Geospatial implementation plan or work package description for agreed priority use cases.
• Configured or developed geospatial data preparation and processing workflows for the confirmed scope.
• Implemented geoprocessing outputs for agreed use cases, such as aggregation, proximity analysis, classification, composite indexing, clipping, or sub-national processing.
• Validated geospatial outputs in agreed formats, such as GeoJSON, Shapefile, CSV with coordinates, GeoTIFF where applicable, map service layers, or API-ready spatial data products.
• Technical documentation and handover package, including workflow descriptions, configuration notes, supported formats, operating guidance, known limitations, and recommendations for future improvements.

• Five years of experience with an advanced university degree in Geographic Information Systems, Geography, Geomatics, Geospatial Science, Environmental Science, Computer Science, Data Science, Engineering, or a related discipline.
• Three years of experience with a first-level university degree combined with additional relevant experience may be accepted.
• Professional experience in GIS, geospatial data engineering, spatial analytics, or geospatial solution implementation.
• Hands-on experience working with raster and vector data, administrative and sub-national boundaries, coordinate reference systems, spatial metadata, and geospatial data quality controls.
• Experience designing and implementing geospatial workflows involving data preparation, reprojection, geometry validation, spatial joins, aggregation, clipping, proximity analysis, buffering, raster processing, and/or map layer publication.
• Experience with common GIS formats and standards, including GeoJSON, Shapefile, KML/KMZ, CSV, and GeoTIFF.
• Experience with web mapping and geospatial service patterns, including WMS, WFS, WCS, OGC API Features, and OGC API Tiles.

The following are required technical skills of the Geospatial Data Scientist:

• GIS desktop, server, and/or open-source geospatial tools such as ArcGIS, QGIS, GDAL/OGR, GeoPandas, PostGIS, GeoServer, MapServer, or equivalent technologies.
• Python for geospatial processing, including libraries such as GeoPandas, Rasterio, Shapely, Fiona, PyProj, Xarray, or similar.
• SQL and spatial SQL, especially with PostGIS, SQL Server spatial, or equivalent spatial database capabilities.
• Cloud-based geospatial processing experience, particularly in Azure, AWS, or Google Cloud environments.
• Experience with data lake or lakehouse architectures and geospatial data integration in analytics platforms.
• Familiarity with metadata standards relevant to geospatial and open data, such as ISO 19115, DCAT/DCAT-AP, Dublin Core, or equivalent.
• Understanding of SDMX, environmental indicators, statistical/geospatial integration, or international reporting frameworks is an advantage.

The following are required competencies of the Geospatial Data Scientist

• Strong problem-solving skills and ability to assess technical feasibility, complexity, risks, and dependencies.
• Ability to communicate geospatial concepts clearly to technical and non-technical stakeholders.
• Strong attention to data quality, reproducibility, documentation, and operational maintainability.
• Ability to work collaboratively with data engineers, data architects, API developers, governance specialists, project managers, and client stakeholders.
• Ability to work independently, manage priorities, and deliver outputs within agreed timelines.
• Awareness of data governance, responsible data management, interoperability, and open data principles.
• Excellent command of written and spoken English.

Desired Certifications:

• Azure Data Engineering related certifications
• Azure Data Scientist Associate

Experience supporting data operations within a mission-critical defense environment. The annual base salary range for this position is anticipated to be $110,000 - $140,000 USD. The listed salary range represents our good faith estimate for this position. Please note that the salary information is a general guideline only. Geocgi considers factors such as (but not limited to) scope and responsibilities of the position, candidate’s education & work experience, training & certifications, and key skills as well as market and business considerations at the time of the offer.

As an employee of geocgi, the Geospatial Data Scientist will have access to a generous benefits package, in addition to a corporate culture and community of GIS geeks. Our benefits include but are not limited to:

• Competitive salaries, commensurate with experience and leading Federal Contractors in the geospatial industry.
• Opportunities for upward mobility in a dynamic fast paced environment within a small company.
• Merit-based spot and end of year bonuses.
• Safe Harbor 401(k) plan with immediate vesting.
• Flexible work hours and PTO.
• Enjoy 100% company-paid medical, dental, and vision premiums for individual employees. Coverage extensions for spouses and child dependents are available for purchase through the company plan.
• Company paid training, certifications, and professional growth and development.