Data Management Research Scientist - Remote Opportunity

About the Role

Join the innovative team at Los Alamos National Laboratory as a Data Management Research Scientist. This remote position allows you to contribute to the development of high-performance data ecosystems that support AI-driven scientific discovery. You will design and implement next-generation data-ingestion pipelines that automatically discover, validate, and catalog heterogeneous scientific datasets across LANL and the broader DOE community.

What You'll Do

• Design and implement data-ingestion pipelines for scientific datasets.
• Develop and maintain open-source software libraries in Python for metadata capture and cataloging.
• Integrate tools into HPC environments to ensure scalable workflows.
• Support metadata schemas using standards such as Dublin Core and DCAT.
• Collaborate with cross-disciplinary teams to translate domain requirements into production-ready data services.
• Publish results in peer-reviewed journals and technical reports.

Requirements

• Minimum of 2 years of programming experience in Python and familiarity with C/C++ and JavaScript.
• Hands-on experience with SQL databases (PostgreSQL, DuckDB) and data-catalog services.
• Familiarity with metadata standards like Dublin Core and DCAT.
• Experience deploying code on HPC clusters and using notebook-based environments like JupyterLab.
• Strong communication skills for presenting work at conferences and meetings.

Nice to Have

• Record of scientific publications or open-source contributions.
• Experience with FAIR data principles and DOE's data-policy ecosystem.
• Active Q clearance is highly desirable.

What We Offer

• Comprehensive relocation support packages.
• Flexible schedules and generous PTO.
• 401(k) plan with matching contributions.
• Medical, dental, and vision insurance options.
• Learning opportunities and tuition assistance.

This Data Management Research Scientist position offers a unique opportunity to work remotely while contributing to significant advancements in data management and AI. If you are passionate about scientific research and data management, apply now to join our team!