
Data Science Engineer
4 weeks ago
Key Responsibilities:
- Analyze and process thermal and optical imagery from satellite and drone platforms.
- Develop data-driven geospatial solutions for applications including:
- Crop health monitoring, water stress detection, and irrigation planning
- Yield prediction using fused thermal and optical data
- Soil moisture estimation and early detection of drought conditions
- Forest fire detection, hotspot mapping, and risk assessment
- Greenhouse gas (GHG) detection and other emission monitoring
- Urban heat island mapping and infrastructure-level thermal assessments
- Design and implement machine learning and deep learning models to extract actionable insights from geospatial datasets.
- Work closely with product and engineering teams to build scalable, real-time solutions that can be deployed in operational environments.
Required Qualifications:
- Master's degree in Data Science, Remote Sensing, Geospatial Data Science, or a related discipline.
- Minimum 3 years of professional or research experience.
- Strong coding skills in Python, with proficiency in libraries such as NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch, and GDAL.
- Solid foundation in remote sensing techniques, image preprocessing, and satellite data analytics.
- Experience applying ML/DL/computer vision techniques to satellite or drone imagery for real-world geospatial applications.
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