Data Science Associate, Ethiopia (Restore Local)

About the role

WRI's Restore Local initiative, aligned with its Food, Land and Water team, is expanding to Ethiopia's Rift Valley to support the Green Legacy and Degraded Landscape Restoration Special Fund, which sets aside 0.5-1% of federal revenue for restoration. As Data Science Associate, you will help build and manage the information system behind the Special Fund, partnering with Ethiopian Forestry Development, the Ministries of Agriculture, Finance and Planning, and other partners. The role is hybrid, with at least 8 days per month in the WRI Country Office in Ethiopia and occasional travel within Ethiopia.

Key responsibilities

• Co-manage the information system for the Special Fund, helping define architecture, data workflows and the monitoring strategy, and train ministry staff to use it
• Contribute to funding proposals and represent WRI in national monitoring discussions and technical committees
• Oversee the quality of geospatial data on proposed projects, correcting polygons and attributes with GIS software and satellite basemaps
• Manage project and monitoring data across WRI and government platforms, and run statistical and geospatial analyses with remote sensing data to help prioritize investments
• Evaluate data products and system outputs, using AI-enabled coding tools to speed quality checks
• Produce maps, dashboards and analyses for project and national reporting
• Research geospatial tools and methods, develop training materials, and contribute to communications on Ethiopia's restoration progress
• Pilot AI-enabled coding and automation to improve data collection, QA/QC and system maintenance

Required profile

• Bachelor's degree in GIS, geography, forestry, environmental science, computer science, data science or a related field
• 6+ years of professional experience in GIS, remote sensing and/or data science, including working with non-specialists on geospatial and data tools
• Experience designing and launching data analysis projects and building data pipelines for large geospatial datasets
• Experience scoping or building online systems for geospatial data collection and monitoring (e.g., ODK/Kobo Collect, Survey CTO)

Required skills

• Python (NumPy, Pandas, GeoPandas) and/or Google Earth Engine, with AI-enabled coding tools such as GitHub Copilot
• GIS software such as ArcGIS Pro, QGIS or GRASS GIS
• Remote sensing and interpretation of satellite imagery
• Proficiency with vector data