Geospatial Resilience Solutions Architect
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Job Description
Geospatial Resilience Solutions Architect developing geospatial modeling workflows for resilience analysis at Versar Global Solutions. Supporting AI-enabled geospatial decision-support applications for environmental management.
Responsibilities:
- Develop and implement geospatial and environmental modeling workflows supporting resilience analysis related to flooding, erosion, wildfire, water security, infrastructure vulnerability, and landscape change.
- Build reusable geospatial, machine learning, and remote sensing pipelines using tools such as Python, ArcGIS Pro, Google Earth Engine, and cloud-based geospatial platforms.
- Integrate diverse environmental datasets including remote sensing products, terrain data, hydrologic information, climate datasets, and field observations into scalable analytical workflows.
- Support development of AI-enabled geospatial decision-support applications and visualization tools for government and commercial clients.
- Coordinate across interdisciplinary technical teams to ensure analytical outputs, visualizations, and technical findings are communicated effectively to both technical and non-technical stakeholders.
- Contribute to project planning, technical execution, and workstream coordination across multiple concurrent projects.
- Support proposal development, technical scoping, white papers, capability development, and identification of strategic partners and collaborators.
- Assist in development of innovative approaches that combine geospatial analytics, environmental science, machine learning, and resilience planning.
- Support the evolution of internal geospatial and resilience analytics capabilities through development of repeatable tools, standards, and workflows.
- Participate in customer engagements, technical briefings, workshops, and collaborative solution development efforts.
Requirements:
- Strong GIS and geospatial analytics capabilities using ArcGIS Pro, QGIS, Google Earth Engine, or similar platforms.
- Proficiency in Python for geospatial analysis, automation, data processing, and/or machine learning workflows.
- Knowledge of environmental systems, earth sciences, hydrology, climate science, landscape processes, or related disciplines.
- Experience integrating remote sensing and spatial datasets into analytical and visualization workflows.
- Familiarity with machine learning techniques and environmental data applications.
- Ability to communicate complex technical findings clearly through maps, dashboards, visualizations, and presentations.
- Strong organizational and coordination skills with the ability to manage multiple technical workstreams simultaneously.
- Demonstrated ability to work effectively within interdisciplinary teams.
- Strong written and verbal communication skills.
- Must be proficient in English, both written and verbal, to ensure effective communication and collaboration.
- Successful results of preemployment screenings, including federal background check, MVR, and drug screen.
- Comply with company drug and alcohol policy.
Benefits:
- Health insurance
- 401(k) matching
- Professional development opportunities
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