| Purpose of the Position: |
UAH is seeking a Data Scientist with applied experience in machine learning, cloud computing, and remote sensing/geospatial data, with a strong emphasis on geospatial foundational models (e.g., Prithvi, SatMAE, Clay, and similar Earth Observation Foundation Models). The scientist will co-develop Earth-observation-driven data solutions and geospatial AI-informed tools, working across the full lifecycle from model fine-tuning/adaptation through deployment.
Duties/Responsibilities
• Develop, fine-tune, and deploy foundational model-based geospatial AI workflows (EO foundation models, vision transformers) against real-world remote sensing problems
• Design and build data science and geospatial AI solutions across a range of thematic application areas
• Process and analyze large geospatial datasets; assess new data sources and data-gathering techniques for suitability with foundation-model pipelines
• Build and maintain cloud/on-prem infrastructure supporting model training, fine-tuning, and inference
• Contribute to open science work: publications, data products/services, and conference presentations
• Collaborate within a cross-disciplinary data science team in a fast-paced, production-oriented environment
• Contribute to technical training/knowledge transfer materials
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| Minimum Requirements: |
• Master's degree in Computer Science, Engineering, Earth Science, Geosciences, Environmental Science, or other highly quantitative discipline (Bachelor's degree and experience in a specialized area may be substituted for a degree) and 1 to 2 years of full-time work experience.
• Minimum of 1 year verifiable full-time work experience in these disciplines.
• Demonstrated, hands-on experience with geospatial/Earth Observation foundational models — fine-tuning, adapting, and deploying models such as Prithvi, SatMAE, Clay, or comparable EO foundation models; strong understanding of Vision Transformer architectures
• Experience developing, tuning, and deploying ML-based algorithms (geospatial AI) to address real-world problems
• Skilled in Python, plus working knowledge of R, JavaScript, C, and SQL
• Infrastructure: Linux server management, AWS (EC2, RDS), Kubernetes, NGINX, THREDDS, GeoServer, Ollama
• API development and Git-based workflows
• Experience with LLM-based workflows (Llama 3, Mixtral), LangGraph, MCP, A2A, and/or broader deep learning approaches
• Earth science/geospatial data analysis: statistical and scientific data processing automation, temporal raster data processing
• Publication record commensurate with experience level
• Comfortable working both collaboratively on a team and independently to deliver
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| Desired Qualifications: |
• 2 or more years of relevant experience working in degreed disciplines is desired.
• Experience working with NASA and/or other federal, state, local, tribal, or private sector organizations is desired.
• Experience writing and developing technical manuscripts
• Strong science communication skills
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