Data Scientist III
Jefferson Lab
Summary
Lead high impact, data driven research that supports mission critical programs across environmental science, climate modeling, nuclear physics, and energy systems. Design advanced statistical and machine learning solutions for complex scientific challenges, build scalable data workflows, and collaborate with interdisciplinary teams to push forward innovation in computational science.
Job description
In this job you will:
- Develop advanced data science models including spatiotemporal statistical frameworks, deep learning architectures, generative models, and probabilistic simulations.
- Build surrogate models, reduced order models, advanced surrogate and probabilistic machine-learning models, and streaming data inference tools for large-scale scientific datasets.
- Design workflows for uncertainty quantification, extreme value analysis, statistical validation, and multi model data fusion.
- Conduct research leveraging high-performance computing, scientific data compression, and scalable analytics in support of exascale computational environments.
- Collaborate with scientists and engineers to translate complex scientific questions into robust computational or statistical solutions.
- Publish research findings in peer-reviewed journals; present work at national and international scientific meetings.
- Lead and contribute to federally funded research programs (e.g., DOE ASCR, SciDAC, BER, NP), serving as PI, Co PI, or institutional lead as required.
Additional Responsibilities
- Support proposal development for data-driven scientific initiatives.
- Contribute to scientific community service, including reviewing journal submissions, proposal evaluations, special issue editing, and participation in professional societies.
- Assist in organizing workshops, symposia, and technical sessions related to data science, machine learning, uncertainty quantification, and environmental modeling.
- Engage in outreach activities such as invited talks, lectures, and panel discussions.
- Mentor postdocs, graduate students, and interns on advanced machine learning, statistical modeling, and computational research topics.
Knowledge, Skills, and Abilities
- Advanced knowledge of statistical modeling, machine learning, generative modeling, and probabilistic simulation.
- Strong mathematical foundations in multivariate analysis, dimension reduction, clustering, and extreme value theory.
- Ability to develop scalable ML/AI workflows for scientific applications.
- Strong communication skills and ability to collaborate across disciplinary teams.
- Ability to design, validate, and interpret complex scientific models.
- Familiarity with scientific Python, HPC environments, and data compression frameworks.
- Ability to support mission-driven research and tight federal deliverables.
Requirements
- 6 or more years in data science, applied statistics, or scientific machine learning
- Demonstrated research contributions in spatiotemporal modeling, deep learning and generative models, or Bayesian inference and probabilistic modeling
- Environmental or geophysical data analysis
- Surrogate modeling and dimensionality reduction
- Extreme-event modeling and uncertainty quantification
- Experience working with large heterogeneous datasets and scientific computing environments
- Experience mentoring junior researchers
- Bachelor's Degree in Statistics, Applied Mathematics, Computer Science, Data Science, Computational Science, or a related field
- Advanced knowledge of statistical modeling, machine learning, generative modeling, and probabilistic simulation
- Strong mathematical foundations in multivariate analysis, dimension reduction, clustering, and extreme value theory
- Ability to develop scalable ML/AI workflows for scientific applications
- Strong communication skills and ability to collaborate across disciplinary teams
- Familiarity with scientific Python, HPC environments, and data compression frameworks
- Must be authorized to work in the United States without current or future employer visa sponsorship
Benefits
- Medical, Dental & Vision
- Flexible Spending Accounts
- Paid Time Off
- Paid Parental Leave
- Vacation
- Holidays
- Sick Leave
- 401(k) 9% Contribution
- Tuition Assistance
- Training & Development
- Flexible Work Arrangements
- Relocation Assistance
Company overview
The Thomas Jefferson National Accelerator Facility, commonly known as Jefferson Lab, is a premier U.S. Department of Energy national laboratory and Federally Funded Research and Development Center (FFRDC) located in Newport News, Virginia. Established in 1984, Jefferson Lab specializes in nuclear physics research, accelerator science and technology, and operates as a major scientific user facility. The laboratory's primary mission is to deliver breakthrough science and technology in nuclear physics through its flagship facility, the Continuous Electron Beam Accelerator Facility (CEBAF), which provides high-quality beams of polarized electrons for fundamental research into the quark and gluon structure of protons and neutrons. With approximately 850 employees and an annual budget of around $238 million, Jefferson Lab serves as a critical resource for the international scientific community, hosting approximately 1,650 researchers annually. The laboratory is expanding its mission to include high-performance computing, data science, and artificial intelligence through the High Performance Data Facility (HPDF) project, positioning itself as a multi-purpose national laboratory. Jefferson Lab plays a leading role in major international collaborations, including the Electron-Ion Collider project, and maintains core capabilities in superconducting radiofrequency technology, experimental detector design, and computational science.