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.

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For more than 50 years, Verisk has helped property and casualty insurers make smarter decisions about risk through AI-powered risk modeling, advanced analytics, and technology solutions spanning the entire policy lifecycle.  We are a leading strategic data, analytics, and technology partner to the global insurance industry, guided by core values of learning, caring, and results while maintaining the highest ethical standards as stewards of the industry's most comprehensive datasets. Learn more about Verisk and what we are doing within the insurance industry. 

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• 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.

Education

• M.Tech / M.Sc / B.Tech in Geo-Informatics, Geography, Remote Sensing & GIS, or a related field in Spatial Technologies

Experience

• 7–10 years of experience in GIS, Remote Sensing, or Geospatial Analytics
• 3–5 years of experience in people management or team leadership
• Proven experience managing complex geospatial projects and coordinating cross-functional teams

Technical Skills

Geospatial Tools & Software

• Expert-level proficiency in ArcGIS Pro, ArcGIS Desktop, QGIS, and Google Earth Pro
• Familiarity with ArcGIS extensions such as Spatial Analyst, 3D Analyst, Image Analyst, and Network Analyst

Programming & Automation

• Advanced proficiency in Python and geospatial libraries (ArcPy, GDAL, GeoPandas, Rasterio, Fiona, Shapely, PyProj etc.)
• Experience with SQL and spatial databases (PostgreSQL/PostGIS)
• Proven ability to develop and maintain automated geospatial workflows

Machine Learning & AI

• Experience applying Machine Learning / Deep Learning techniques to geospatial datasets (e.g., classification, object detection, spatial clustering)
• Familiarity with scikit-learn, TensorFlow, or PyTorch

Data Handling & Analysis

• Strong experience working with raster, vector, and LiDAR datasets
• Ability to derive insights from large and complex geospatial datasets, with a focus on scalable processing, performance optimization, and continuous enhancement of spatial analysis and modelling workflows.

Communication & Collaboration

• Strong communication skills for technical reporting and cross-functional collaboration
• Ability to work effectively in global and distributed team environments
• Strong organizational and time management skills to manage multiple priorities and deliverables

Preferred / Desirable Skills

• Experience with WebGIS platforms, ArcGIS Enterprise, or other web mapping technologies
• Familiarity with HTML, Java, MATLAB, Power BI, or ProjectPlace
• Understanding of geostatistical techniques, spatial modelling, and data mining
  Exposure to catastrophe modelling, insurance analytics, or risk analytics domains