Data Scientist I

At Jefferson Lab,you'llchampioncutting-edgescience and operational excellence while shaping the future of discovery. Join us and make your mark - where excellence meets purpose, andgreat mindstruly matter.

The good-faith pay range for this role is $80,300 - $ 142,300 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.

This position is not eligible for employer visa sponsorship. Applicants must be authorized to work in the United States without current or future employer visa sponsorship.

What your job will be like:

Work on all elements of the data science workflow (data preprocessing, analyzing data using exploratory mathematics, statistical techniques, developing and optimizing AI/ML models, developing agentic workflows). Recommend various technology options or approaches for system and processes improvements in terms of performance, efficiency, cost or safety.

In this job you will:

• Participate in the research and development in machine learning and data science focused on applications such as:
• AI/ML based active control of large complex systems
• Surrogate modeling of particle accelerator processes, deployment and continual learning workflows
• Uncertainty Quantification for ML
• Conduct technical research in areas of interest to the projects.
• Publish research results in highly visible, peer-reviewed venues (conferences, workshops & journals).
• Develop and maintain high quality software for data science projects (machine learning, continual learning, uncertainty quantification).
• Interact with internal and external researchers and domain scientists for collaboration purposes.
• Participate and potentially lead technical presentations on the work.
• Participate in team meetings and develop ideas for new projects/proposals.

Experience

• Required: none
• Preferred: 2 or more years of postdoc experience
• Preferred: experience with contributing and leading tasks on large projects with multi-disciplinary teams.

Education

• Required: Bachelor's Degree Computer Science, Data Science, Applied Mathematics, Computer Engineering, or a closely related technical area
• Preferred: Ph.D.

Experience and Education Exchange

Education above the minimum may be substituted for experience. Relevant experience may not be substituted for education.

Knowledge, Skills, and Abilities

• Proficiency in Python and familiarity with publicly available technical libraries for data analytics (e.g. scikit-learn), deep learning (e.g. Pytorch, Tensorflow) and optimization tools
• Proficiency in advance machine learning such as uncertainty quantification for ML, continual learning, graph neural networks
• And/or proficiency in agentic workflow tools such as LangChain, LangGraph
• Ability to operate computer equipment in an office or laboratory environment
• Strong interpersonal skills and ability to effectively work on project teams
• And/or proficiency in Large Language Models training and evaluation
• 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, software, documents or other work products
• Ability to clearly communicate and report the progress on tasks and projects

About Jefferson Lab

Join a community with a common purpose of solving the most challenging scientific and engineering problems of our time. The Jefferson Lab campusis located insoutheasternVirginiaamidst a vibrant and growing technology community.

A career at Jefferson Lab is more than a job. You will be part of "big science" and work alongside top scientists and engineers from around the world unlocking the secrets of our visible universe. Managed by SURATech, LLC, Thomas Jefferson National Accelerator Facility is entering an exciting period of mission growth and is seeking new team members ready to apply their skills and passion to have an impact. You could call it work, or you could call it a mission. We call it a challenge. We do things that will change the world.

Total Rewards at Jefferson Lab

At Jefferson Lab, we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Our benefits program includes, but is not limited to:

• Medical, Dental, and Vision Care Plans
• Flexible Spending Accounts
• Paid Time-off and Leave Programs (Paid Parental, vacation, holidays, and sick leave)
• 401(k) Plan - 9% Lab Contribution; 100% vested
• Flexible Work Arrangements
• (Remote & Alternate Work Schedules available)
• Tuition Assistance, Training and Professional Development Programs
• Live near the waterways of the Chesapeake Bay region with access to nearby beaches,
• mountains, and all major metropolitan centers on the East Coast

SURATech, LLC manages and operates the Thomas Jefferson National Accelerator Facility (Jefferson Lab). SURATech is an Equal Opportunity Employer.

SURATech is committed to providing reasonable accommodation for people with disabilities (unless doing so will result in an undue hardship). If you need a reasonable accommodation for any part of the employment process, please send an e-mail to View email address on click.appcast.io or contact Human Resources by calling View phone number on click.appcast.io and selecting option 1 between 8 am - 5 pm EST to provide the nature of your request.

Employment with SURATech is conditional upon DOE approval if at any time during your employment you are participating in a Foreign Government Talent Recruitment Program or Affiliated activity. Generally, such programs/activities include any foreign-state-sponsored attempt to acquire U.S.-funded scientific research through programs run or funded by the government that target scientists, engineers, students, academics, researchers, and entrepreneurs of all nationalities working or educated in the United States. This includes positions or appointments, both domestic and foreign, titled academic, professional, or institutional appointments whether or not remuneration is received and whether full-time, part-time or voluntary.