GIS Modeller

Skills and Competencies

Strong foundation in machine learning, computer vision, and numerical methods

Experience with CNN-based architectures and modern vision models

Solid understanding of remote sensing techniques, including:

o Image classification and segmentation

o Change detection and decorrelation

o Processing of hyperspectral and multispectral imagery

Proficiency in Python, with hands-on experience in:

o Machine Learning frameworks: Scikit-Learn, TensorFlow, Keras, PyTorch, GluonCV

o Computer Vision, Image Processing & Geospatial libraries: OpenCV, GDAL, GeoPandas, Rasterio, Rasterstats, Shapely, Fiona, NumPy, Pillow

o Data Processing & Analytics: Pandas, NumPy, SciPy

o Visualization: Matplotlib, Seaborn, Plotly

Familiarity with GIS tools: ESRI suite, QGIS, GRASS

Exposure to Google Earth Engine is a plus

Education
Post-graduation (Masters/PhD) in Geoinformatics, Remote Sensing, Earth Sciences, Computer Science or Graduate in Civil Engineering, Computer Science, Environmental Science from an institute of good repute. Candidates with 1–2 years of relevant experience would be preferred.

Responsibilities

Develop scalable GeoAI pipelines for large-scale satellite and aerial imagery using AI/ML, computer vision, and remote sensing.

Develop and apply vision models and LVMs 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

Develop and analyze high-resolution datasets including LULC, buildings, infrastructure, and renewable energy assets.

Support model evaluation, visualization, metadata, documentation, and productionization of GeoAI solutions.

About the team

Our Geospatial Team (Model Development Group) is responsible for developing critical geospatial datasets, exposure intelligence, and modeling components that underpin Moody’s industry-leading catastrophe risk solutions used by more than 400 clients worldwide. By joining our team, you will be part of exciting work in developing geospatial datasets for catastrophe models, advancing AI-powered geospatial analytics, and delivering innovative solutions in renewable energy intelligence, event response, and damage assessment to support global risk insights and decision-making.