GIS Associate
Farmers for Forests
About Us
F4F is a Hybrid Social Enterprise working to protect and increase India’s biodiverse forest cover in close collaboration with rural communities. Founded in December 2019, F4F is one of the few organizations in India working in the forestry sector and using a payment-for-ecosystem services model for its environmental protection and restoration activities.
F4F was incubated at Mulago, Fast Forward, NSRCEL-IIMB, The Nudge Institute and Shakti - The Empathy Project. Our work has been supported by several organizations including Accenture, ACT Grants, Opus Software Solutions, Rainmatter Foundation and Rohini Nilekani Philanthropies.
We have also featured on DW TV and Scroll's Eco India series as well as DW Hindi. We have also been selected as one of India's top innovators working in the ecosystem restoration and conservation sector by the World Economic Forum.
Job Description
We are looking for a motivated and detail-oriented GIS Associate to support spatial data management and analysis for F4F’s carbon and agroforestry projects. The role includes verifying KML and spatial data, assisting in AI model training through annotation, and performing core GIS tasks such as mapping, visualization, and spatial analysis. This position is ideal for a fresher or early-career professional passionate about applying GIS and remote sensing for environmental impact.
Roles & Responsibilities
Verify KML and spatial datasets, ensuring geometric accuracy.
Support annotation for Land Use and Land Cover (LULC) models and validate training data.
Perform GIS operations including mapping, visualization, digitization, and analysis.
Manage geospatial data—organizing, cleaning, and updating shapefiles, rasters, and metadata.
Use Python and GIS libraries (e.g., GeoPandas, rasterio, shapely) for automation and reporting.
Requirements
Fresher or early-career professional passionate about GIS and environmental applications.
Academics in Engineering, Geoinformatics, Geography, Environmental Science, Remote Sensing, or related fields.
Working knowledge of ArcGIS/QGIS and common GIS data formats.
Basic understanding of coordinate systems and spatial analysis.
Exposure to Python scripting and GIS libraries (GeoPandas, rasterio, Fiona).
Detail-oriented, organized, and focused on data accuracy.