Spatial Data Scientist / Geospatial Analyst

Role: Spatial Data Scientist / Geospatial Analyst

Location: Remote

Duration: 2 Months+ Contract

Salary Range: $120,000 to 130,000/Annual

Coding - Python, SQL, Geo Pandas- some core analytics coding skillset required

Role Summary:

We are seeking a skilled Spatial Data Scientist / Geospatial Analyst to design, build, and maintain geospatial tooling and analysis functions using ArcGIS Enterprise and other geospatial platforms. This role will support client's team by providing ongoing and ad hoc geospatial analyses, leveraging data center locations, energy infrastructure, parcel data, and other relevant datasets to drive business insights.

This role bridges data science, spatial analytics, and GIS application development-helping decision-makers understand geographic patterns, optimize infrastructure, and forecast spatial change.

Key Responsibilities:

• Perform advanced geospatial analyses including spatial statistics, network modeling, proximity analysis, and raster processing.
• Develop predictive and spatial-statistical models (e.g., site suitability, spatial clustering, accessibility modeling, network optimization, spatial regression).
• Perform multi-scale spatial analysis using raster and vector datasets, including proximity modeling.
• Lead geospatial data analysis and modeling using ArcGIS Enterprise, ArcGIS Pro, Excel, SQL databases, and other geospatial tools.
• Utilize ArcGIS Pro toolkits (Spatial Analyst, 3D Analyst, Network Analyst, Geostatistical Analyst) for advanced spatial analysis.
• Design compelling data visualizations that communicate spatial patterns, uncertainty, and model outputs to both technical and non-technical audiences.
• Collaborate with cross-functional teams to produce geospatial analyses, maps, and derivative reports for business stakeholders.
• Apply advanced statistical and geospatial analysis techniques to diverse datasets.
• Establish, document, and continuously improve business processes related to geospatial data management and analysis.
• Manage recurring reporting processes, ensuring timely and accurate updates.
• Communicate technical findings and recommendations clearly to senior audiences, both verbally and in writing.

Ideal Candidate

• Demonstrates strong problem-solving skills and a structured, logical approach to complex issues.
• Proficient in communicating technical concepts and research findings to both technical and non-technical audiences.
• Experienced in working independently, managing processes and timelines, and seeking feedback as needed.
• Skilled at managing multiple complex priorities efficiently and with strong attention to detail.
• Creative and proactive in approaching complex research questions and data analyses.
• Experienced in building and maintaining standardized processes, databases, dashboards, and analytical tools.
• Demonstrates strong cross-functional partnership and collaboration skills.

Top 3 Must have skills:

• Minimum 8 years of experience as Data Scientist
• should be able to conduct analysis - used gs spatial tools
• scope and complete data analysis

Good to have:

• Master's degree in a relevant field.
• Experience with remote sensing, LiDAR, or image analysis.
• Experience with cloud-based analytics platforms and geospatial data storage.
• Prior experience supporting infrastructure, energy, or data center projects

Education & Experience:

• Bachelor's degree in Geography, Data Science, Mathematics, Business Management, Economics, Finance, Human Resources, or a relevant field required.
• 2+ years of experience in geospatial analytics, data science, or a related field.
• Proficiency in ArcGIS Enterprise, ArcGIS Pro, and geospatial data analysis tools.
• Experience with SQL databases, Excel, and dashboard/reporting tools.
• Familiarity with geospatial programming libraries (e.g., Python, R) and data formats (Shapefiles, GeoJSON, CSV).

Preferred Qualifications:

• Master's degree in a relevant field.
• Experience with remote sensing, LiDAR, or image analysis.
• Experience with cloud-based analytics platforms and geospatial data storage.
• Prior experience supporting infrastructure, energy, or data center projects.