Geospatial Analyst

A Remote Sensing Specialist will contribute to project development, feasibility evaluation, implementation, and ongoing monitoring. The role involves analyzing and modeling remote sensing and geospatial data for various applications such as land cover/use mapping, fire risk assessment, above-ground biomass estimation, and deforestation risk modeling.

• Support project design, feasibility assessment, implementation, and long-term monitoring
• Analyze & model remote sensing & geospatial data for applications such as land cover/use mapping, fire risk assessment, above-ground biomass estimation, and deforestation risk modeling.
• Leverage cutting-edge technologies including cloud computing, machine learning, and scripting languages (Python, JavaScript, SQL) to build automated workflows, enhance geospatial infrastructure, and support MRV processes.
• Support field data collection through drone coordination and validation activities, provide technical guidance and training, and ensure geospatial quality control across teams.

• Design and implement project workflows using advanced technologies.
• Build and deploy automated workflows to enhance geospatial infrastructure.
• Model and analyze remote sensing and geospatial data for various applications.
• Ensure geospatial quality control across teams.
• Provide technical guidance and training to support field data collection.

• Bachelor's degree in GIS, Environmental Science, Forestry, Computer Science or related fields.
• At least 5 years of experience in Remote Sensing & GIS.
• Experience and expertise in workflow automation, machine learning/deep learning techniques for image classification and segmentation.
• Experience in advanced remote sensing analysis and modeling i.e., image processing both active and passive sensors.
• In-depth knowledge and experience of RS/GIS implementation for forestry conservation land use in AFOLU carbon projects.
• Familiarity with photogrammetry software.
• Programming skills particularly in Python and Google Earth Engine.
• Familiarity with terms such as land cover land use and carbon project modeling.