The good-faith pay range for this role is $118,400 - $186,850 per year. Actual compensation may vary and may be above the posted range based on factors such as a candidate's skills, experience, education, certifications, and work location.

What your job will be like:

Join Us in Shaping the Future of Scientific Discovery

Are you driven by the belief that high quality, well governed data accelerates breakthrough science? Do you want your work to directly influence national research infrastructure and empower scientists across disciplines? We are seeking a mission focused leader who is passionate about FAIR (Findable, Accessible, Interoperable, Reusable) data, stewarding complex scientific information, and advancing the practices that make research data AI ready and highly actionable.

About the Role

This position sits in the Office of the Chief Data Officer in the Data and Computational Sciences Directorate. This is a unique opportunity to lead project-focused research teams and efforts that advance the FAIR and AI-readiness of data produced at the lab and beyond. This position also contributes to the High Performance Data Facility (HPDF)-a first-of-its-kind, distributed DOE ASCR user facility that will define the future of scientific data management and AI enabled discovery. As part of the HPDF early user engagement team, you will help shape both the technical architecture and organizational strategy of a national facility dedicated to transforming how scientific data is stored, governed, shared, and used.

Key Responsibilities:

Research and Data Leadership: Advance the frontiers of FAIR, machine actionable, and AI ready data models and workflows that enable compliant, high value research. Advance metadata, provenance, data architecture, stewardship frameworks, and data life cycle practices for both research and operational data.

HPDF Early User Engagement & Design: Collaborate with early HPDF user communities to identify governance needs and translate them into technical and policy requirements. Contribute to the design of HPDF's organizational structures, data governance models, metadata/cataloging approaches, and user-facing data services.

Policy, Governance, & Standards Development: Serve as a subject matter expert advising lab leadership on data governance, investment priorities, and compliance requirements. Lead the development of lab wide and DOE-level standards, FAIR initiatives, and cross-laboratory data interoperability efforts.

Ideal Candidate Profile:

We are looking for someone who is inspired by mission-driven scientific work and the opportunity to strengthen the national ecosystem of research data. Thrives at the intersection of data science, research infrastructure, and organizational strategy. Understands FAIR principles deeply and sees their implementation as a catalyst for discovery and AI-accelerated science. Develops effective strategies for metadata standards, provenance capture, data lifecycle design, or scientific data management. Communicates effectively with researchers, executive leadership, and sponsors-translating needs, aligning stakeholders, and building consensus. Is energized by contributing to foundational national projects like HPDF that will support the next era of AI-enhanced science. Is able to develop and engage in novel areas of research as evidenced by a strong publication record in relevant fields. Is able to lead research project teams with clear strategies, goals, and timelines.

In this job you will:

• Use expertise in multiple areas of research data management, stewardship, FAIR and AI ready data, especially for DOE mission. Recommend improvements and solutions to enhance data and software management for lab and HPDF needs.
• Communicate technical material and impact of research findings in written and oral presentations in collaboration meetings, to lab leadership, and in professional conferences and other venues.
• Collaborate and lead projects that advance the frontiers of FAIR data. Provide strategy for project executing: meta/data models and ontologies, and success metrics. Interact with HPDF early users and contributes to HPDF design.
• Identify new research opportunities and directions. Contribute and lead the development of research proposals, articles, and software, and contribute to office strategy.
• Manage work with clear documentation, formal standards. Demonstrate best practices in information sharing and protection. Train and mentor others in these skills.

Experience

• Required: 6 or more years Relevant IT Field Or
• Required: 6 or more years As a data scientist in a research setting. Familiarity with research data processing and analysis workflows
• Required: Experience with contributing and leading tasks on major projects with multi-disciplinary teams.
• Required: Experienced with AI-assisted programming, AI-supportive development workflows, and AI skills development.

Education

• Required: Bachelor's Degree Computer Science, Data Science, Applied Mathematics, Computer Engineering, Or closely related field
• Preferred: Master's Degree

Experience and Education Exchange

Education above the minimum may be substituted for experience.

Knowledge, Skills, and Abilities

• Strong proficiency in Python and understanding of publicly available technical libraries for data analytics (e.g. scikit-learn, Pandas), deep learning (e.g. Pytorch, Tensorflow) and optimization tools.
• Ability to work with large datasets and mine relevant information for use in AI/ML applications.
• Proactive, highly motivated self-starter.
• Ability to develop approaches and solutions to complex problems in the forms of proposals, publications, software, documents or other work products.
• Ability to operate computer equipment in an office or laboratory environment.
• Ability to clearly communicate and report the progress on tasks and projects in writing and through presentations.
• Strong interpersonal and leadership skills and ability to effectively work on collaborative project teams.
• Self-motivated and works independently as well as part of a team. Ability to manage up, alerting supervisor and other project staff when work is waiting on additional information or when there are issues threatening deadlines or other milestones.
• Strong organizational skills.
• Sustain strong coding skills and uses AI assisted development.