Senior Geospatial Data Scientist

Overview

In this contract role, you will advance geospatial analytics within a global team focused on masterplanning, digital twins, and data-driven insights. You’ll translate large geospatial datasets into actionable outcomes for diverse client projects. The work blends research, development of automated GIS solutions, and stakeholder-facing demonstrations of GIS capabilities. You’ll contribute to cross-functional initiatives and help shape scalable geospatial data products and workflows.

Pay / Benefits

• flexible working patterns
• hybrid work arrangement
• diverse project exposure
• opportunity to work globally
• competitive compensation
• supportive team culture

Responsibilities

• Perform R&D on geospatial services and new technologies
• Develop 3D virtual cities and digital twins; create new data products and insights
• Manage complex masterplanning projects with data governance
• Set GIS standards and disseminate templates for mapping
• Lead GIS training and develop templates, styles, and symbology
• Bid management for RfW: scope writing, cost estimation, resource planning
• Develop web mapping solutions using AI/ML and integrate datasets into gaming engines

Key requirements

• Geospatial data analytics experience and ability to derive insights from big data
• Proficiency in Python, R, SQL, and data-science tools; experience with spatial data processing
• Experience with ArcGIS/ArcPy, QGIS, Shapely, GeoPandas, NumPy, Pandas, Matplotlib
• Experience setting up spatial databases (PostgreSQL/PostGIS, MS SQL Spatial) and other big data platforms like MongoDB
• Familiarity with Vector Databases and ETL for CAD/BIM to GIS workflows
• Cloud computing knowledge (Azure, AWS, Oracle Cloud) and cybersecurity basics
• Experience with OpenCV and FME for computer vision and GIS workflows
• NLP exposure for clustering/pattern recognition; ability to communicate methodologies to diverse audiences
• Strong problem-solving abilities
• Self-starter with proactive mindset
• Ability to communicate complex analyses to technical and non-technical stakeholders
• 3D GIS and digital twin technologies
• AI/ML integration in geospatial contexts
• Open-source geospatial libraries (GeoPandas, Shapely, scikit-learn)

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