Earth Science Data Scientist — AI/ML & Data Systems

The University of Alabama in Huntsville; Alabama; On-site; USD 89,000 - 94,000; Full time

Job summary

The University of Alabama in Huntsville seeks a data science specialist to advance NASA Earth science data management and dissemination within the ODSI. You will bridge research and operational systems, curating data and validating AI/ML workflows.

The role requires a strong computational background, experience with geospatial data, and a track record of peer‑reviewed publications. Collaboration across disciplines will be essential to improve Earth data lifecycles.

Qualifications

• Master’s degree or higher in a relevant field with strong research credentials.
• 2.5–3 years of full-time, verifiable professional experience.
• Extensive experience with geospatial datasets and technologies.
• Hands-on experience with numerical Earth science modeling.
• Proven record of peer‑reviewed publications.
• Strong Python, C/C++ or similar languages.

Responsibilities

• Prepare and curate validation datasets for AI and machine learning model development.
• Evaluate model performance using statistical and computational methodologies.
• Identify and define new use cases for AI applications across Earth science domains.
• Develop and implement software solutions across multiple projects in both research and operational contexts.

Skills

Python

C/C++

Geospatial analysis

Machine learning

Scientific computing

Communication skills

Interdisciplinary reasoning

Education

Master’s degree in Atmospheric Science, Earth Science, Remote Sensing, or related field

Ph.D. in Atmospheric Science, Earth Science, Remote Sensing, or related field

Tools

Geospatial data tools

Numerical modeling

Job description

The University of Alabama in Huntsville seeks a data science specialist to advance NASA Earth science data management and dissemination within the ODSI. You will bridge research and operational systems, curating data and validating AI/ML workflows.

The role requires a strong computational background, experience with geospatial data, and a track record of peer‑reviewed publications. Collaboration across disciplines will be essential to improve Earth data lifecycles.