| Purpose of the Position: |
The Office of Data Science and Informatics (ODSI) within the Laboratory for Applied Science (LAS) at the University of Alabama in Huntsville (UAH), seeks a highly skilled Data Scientist with solid foundation in data science, computational methods, and some experience in physical science experimentation workflow, with the ability to work across disciplinary boundaries to enhance NASA’s scientific data lifecycle including, but not limited to, data acquisition and management, curation, dissemination, analytics, and AI enabled curation and discovery capabilities.
This role will provide technical leadership and will contribute to ODSI’s mission of evaluating emerging trends in data science and informatics, shaping strategic direction, and developing scalable, user-centered solutions for NASA’s Physical Sciences research community.
ODSI evaluates trends across data science and informatics communities to inform strategic direction and develop effective, scalable solutions. The office also provides a user-centered perspective on how Earth science data are represented, communicated, and utilized. The position contributes to cross-disciplinary collaboration aimed at improving all phases of the Earth science data lifecycle, including policy, engineering, workflows, and information delivery.
Duties / Responsibilities:
• Lead Data Publication & Curation Pipelines:
Serve as the technical lead for end-to-end scientific data publication workflows, including data ingestion, curation, metadata enhancement, and quality assurance. Manage publication schedules, track workflow progress, resolve data readiness issues, and ensure timely release of datasets aligned with NASA program requirements. Explore improvements in data curation workflows and scientific metadata standards.
• Principal Investigator & Submitter Engagement:
Act as the primary liaison for Principal Investigators, data providers, and development teams. Provide expert guidance on data standards, submission protocols, and best practices for scientific data stewardship. Support improvements to data submission systems and user experience.
• Data Lifecycle Reporting & Analytics:
Track and communicate data publication status, quality metrics, workflow performance indicators, and risk assessments to project and division leadership. Apply data science analytics to improve operational insight.
• Scientific Data System Development:
Collaborate with system architects and developers to design and enhance cloud native scientific data systems supporting ingestion, validation, metadata management, and publication. Contribute to architectural decisions that improve scalability, reliability, and usability. Engage in cloud-based data engineering and scientific workflow automation.
• AI/ML for Scientific Data:
Prepare datasets for AI/ML applications, including vectorization, retrieval systems, analytics platforms, and model training pipelines. Conduct applied research and prototype emerging AI/ML approaches to improve scientific data discovery, access, and analysis. Explore AI for scientific data and ML-enabled data curation.
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| Minimum Requirements: |
• Master's degree in data science, informatics, and scientific data workflows, or a related field.
• Minimum of 9.5 years of full-time, verifiable work experience.
• Demonstrated experience in data curation, data stewardship, data lifecycle optimization, and metadata quality.
• Working knowledge of AI/ML models for curation, scientific data analytics, and cloud-based data systems
• Excellent communication skills, including technical writing and formal presentations, with the ability to function within a collaborative, cross-disciplinary team.
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| Desired Qualifications: |
• PhD in data science, informatics, and scientific data workflows, or a related field, is desired.
• Familiarity with NASA Physical Sciences projects in one or more areas such as Fluid Physics, Materials Science, Biophysics, Combustion Science, Soft Matter, or Fundamental Physics will be an added advantage.
• Experience with physical science experimentation or laboratory workflows is a strong advantage.
• Experience in proposal development, technical writing, oral presentation, and communicating complex data concepts is desired.
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