GIS Manager

We are seeking an experienced Manager – GIS / Remote Sensing with 7–10 years of experience to lead geospatial initiatives supporting catastrophe risk model development within the Catastrophe & Risk Solutions (CRS) team. The role requires strong expertise in GIS, Remote Sensing, LiDAR data processing, spatial databases (SQL/PostgreSQL/PostGIS), WebGIS, and Python-based geospatial automation, along with experience applying AI/ML techniques for geospatial analytics.

• Lead the design, development, and integration of GIS, Remote Sensing, and LiDAR-based data workflows supporting country/continental scale catastrophe risk models, delivering high-resolution, location-level geospatial analysis and insights.
• Manage and mentor a team of GIS engineers and analysts, providing technical guidance, performance feedback, and career development support.
• Collaborate with cross-functional teams across Hyderabad and Boston (DTG & Exposure teams) to ensure alignment, effective communication, and timely delivery of project milestones.
• Represent the team in cross-functional discussions, project reviews, and planning meetings, contributing to technical strategy and innovation initiatives.
• Oversee project planning, task allocation, progress tracking, risk management, and delivery timelines to ensure successful execution of geospatial projects.
• Manage and maintain large-scale geospatial datasets, ensuring high standards of data quality, structure, governance, and usability.
• Design and manage spatial databases using SQL, PostgreSQL, and PostGIS to support efficient storage, querying, and analysis of geospatial data.
• Perform and oversee complex spatial data processing tasks including digitization, geo-referencing, projection transformations, and raster/vector data processing.
• Conduct and guide advanced remote sensing analysis, including satellite imagery interpretation, image classification, object-based analysis, and LiDAR data processing.
• Develop and support WebGIS applications and geospatial services for visualization, analysis, and dissemination of geospatial data.
• Oversee the sourcing, integration, and validation of elevation, land use, soil, infrastructure exposure, and other geospatial datasets from national and international data platforms.
• Develop automated geospatial workflows using Python and geospatial libraries to improve efficiency, scalability, and reproducibility.
• Apply Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning techniques for geospatial analytics such as building footprint extraction, land cover classification, and object detection.
• Interpret and validate analytical results, presenting insights through maps, dashboards, WebGIS platforms, and technical reports.
• Prepare and review technical documentation, SOPs, workflow documentation, and project deliverables.