Assc Analytics & Model Analyst - Geo Modeler

Experience level: Experienced Hire

Job category: Data, Analytics & Research

Job sub category: Modeling

Line of business: Insurance

Responsibilities

• Develop scalable GeoAI pipelines for large-scale satellite and aerial imagery analysis using AI and ML, computer vision, and remote sensing techniques
• Develop and deploy scalable GeoAI pipelines and vision models that power large-scale geospatial analytics, exposure intelligence, and catastrophe risk solutions
• Develop and apply vision models and large vision models for segmentation, object detection, building footprint extraction, renewable asset detection, image enhancement, and change detection
• Integrate Generative AI and Agentic AI into geospatial data discovery, analysis, and production workflows
• Build and automate spatial processing pipelines using Python and modern software development practices
• Develop and analyze high-resolution datasets including land use and land cover, buildings, infrastructure, and renewable energy assets
• Support model evaluation, visualization, metadata management, documentation, and productionization of GeoAI solutions

Education

• Post-graduate degree (Masters or PhD) in Geoinformatics, Remote Sensing, Earth Sciences, Computer Science, Data Science, Artificial Intelligence or Machine Learning from a reputable institution

Skills and Competencies

• Geospatial analytics, GeoAI, machine learning, computer vision, including CNN-based architectures and modern vision models
• Remote sensing techniques, including image classification, segmentation, change detection, decorrelation, and processing of hyperspectral and multispectral imagery
• Proficiency in Python with hands-on experience across ML frameworks (Scikit-Learn, TensorFlow, Keras, PyTorch, GluonCV), computer vision and geospatial libraries (OpenCV, GDAL, GeoPandas, Rasterio, Rasterstats, Shapely, Fiona, NumPy, Pillow), data processing/analytics tools (Pandas, NumPy, SciPy), and visualization libraries (Matplotlib, Seaborn, Plotly)
• Familiarity with GIS tools including the ESRI suite, QGIS, and GRASS; exposure to Google Earth Engine is a plus
• Demonstrated proficiency in AI concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency; ability to implement AI-powered solutions; growing awareness of AI risk management and commitment to responsible and ethical AI use

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