GIS Analyst

Domain, Bengaluru Experience 0-2 Location Bengaluru Description We are looking for a Geospatial Analyst to conduct spatial analysis and support research on climate, energy, and sustainability issues. The role will involve managing and analysing complex spatial datasets, developing GIS methodologies, and creating maps, dashboards, and visualisations. The candidate will work closely with researchers and policy experts and contribute to research reports, policy briefs, and academic publications. Responsibilities Conduct spatial analyses to support project objectives and address research questions. Manage and process large and complex spatial datasets using GIS tools such as GEE, ArcGIS Pro, and QGIS. Develop and refine GIS research methodologies, ensuring scientific rigour and reproducibility. Create maps, dashboards, and data visualisations for reports, presentations, and interactive web applications. Collaborate with researchers and policy experts to integrate geospatial insights into broader research initiatives. Contribute to and author research reports, policy briefs, and academic publications. Maintain clear documentation of data sources, methodologies, and analytical workflows. Qualifications and Experience A master’s degree in geography, GIS, environmental science, data science, or a related field with at least 1 year of relevant professional experience; or a bachelor’s degree with at least 4 years of relevant experience. Proven experience in conducting spatial analyses and leading GIS projects from conception to completion. Skill Set Strong analytical and problem-solving skills, with keen attention to detail Excellent written and verbal communication skills A genuine interest in applying geospatial skills to climate, energy, and sustainability issues Familiarity with Google Earth Engine (GEE) for accessing and processing satellite imagery is desirable Basic programming skills, preferably in Python, including tools such as Pandas, GeoPandas, and Rasterio Understanding of remote-sensing concepts, including spectral indices such as NDVI and NDBI, will be preferred Working knowledge of Geo-AI and machine learning techniques A portfolio of academic or personal projects, such as a GitHub repository or online map portfolio, would be an added advantage Duration 24 months