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Job Details
Data Scientist
Job ID #: 12324 Location: Newport News, VA
Functional Area: Science Division: Computational Sciences and Technology (CST) Division
Position Type: Term Education Required: Doctorate (Professional)
Experience Required: Less than 1 year Relocation Provided: Yes

SALARY RANGE:   $58,300 - $87,500 (PD)

Under the general direction, the candidate will be expected to work on all elements of the data science workflow (data preprocessing, analyzing data using exploratory mathematic and statistical technique, and developing and optimization models). Assignments include smaller projects or as a team member on larger projects. Demonstrates initiative in determining solutions to problems and provides clear reports on project progress and completion. Recommends various technology options or approaches for system and processes improvements in terms of performance, efficiency, cost or safety.  

Essential Job Functions:   

The Data Science Department at Jefferson Lab seeks a data scientist to participate in the research and development in machine learning and data analysis focused on applications such as:  

  • Reinforcement learning for non-linear complex control applications  

  • Robust and scalable Machine Learning (ML)/Artificial Intelligence (AI) solutions 

  • Anomaly and fault detection for scientific user facilities  

The 2+ year appointment (contingent on continued funding) will focus on DOE funded projects aimed at applying ML/AI to relevant DOE mission projects, such as DOE Scientific User Facilities.   

Discipline, principal job duties/expectations, and qualitative and quantitative measures of performance: 

  • Conduct technical research in areas of interest to the projects

  • Publish research results in highly visible, peer-reviewed venues (conferences & journals) 

  • Develop and maintain high quality software for machine learning projects 

  • 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 interact with funding clients

The candidate will have a background in a relevant area of computer science and/or data science and some experience with ML/AI. Applicants must be able to work with a diverse group of subject matter experts, possess good communication skills, and have relevant technical knowledge. 


Education, Certifications and Experience: 

  • Ph.D  degree in Computer Science, Data Science, Applied Mathematics, Computer Engineering, or a closely related technical area. 

  • Peer-reviewed publication record in Data Sciences, Machine Learning or a closely related area 8,300 - $87,500

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. PytorchTensorflow) and optimization tools.  

  • Ability to work with large datasets and mine relevant information for use in AI/ML applications 

  • Proactive, highly motivated self-starter with demonstrated experience with contributing and leading tasks on major projects with multi-disciplinary teams. 

  • Demonstrated ability to develop approaches and solutions to complex problems in the forms of proposals, software, documents or other work products. 

  • Must be able to operate computer equipment in an office or laboratory environment 

  • Ability to clearly communicate and report the progress on tasks and projects 

  • Strong interpersonal skills and ability to effectively work on project teams   

JSA will not sponsor H1B visas for this position

• Ability to comprehend, formulate, and communicate highly abstract concepts
• Ability to express or exchange complex ideas by means of spoken and written communication
• Ability to analyze and interpret complex data and develop models

• Ability to traverse across various locations on the laboratory site and access work areas
• Ability to lift up to 10 pounds frequently and 25 pounds occasionally
• Ability to stoop, bend over and climb ladders
• Ability to work on a computer for extended periods
• Visual capabilities sufficient to use computer workstations, read documents, and see safety alarms
• Auditory capabilities to hear safety alarms

Jefferson Science Associates, LLC (JSA) manages and operates the Thomas Jefferson National Accelerator Facility (Jefferson Lab). JSA is an Equal Opportunity Employer and does not discriminate in hiring or employment on the basis of race, color, religion, ethnicity, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, or veteran status or on any other basis prohibited by federal, state, or local law. As part of the JSA’s equal employment opportunity policy, we also take affirmative action as called for by applicable laws and Executive Orders to ensure that minority group individuals, females, disabled veterans, recently separated veterans, other protected veterans, Armed Forces, and qualified disabled persons are introduced into our workforce and considered for promotional opportunities.

JSA is committed to providing reasonable accommodations for persons 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 or call (757) 269-7598 to provide the nature of your request. Reasonable accommodations are considered on a case-by-case basis.

Employment with JSA 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.

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