Applied Statistics Research Staff Member

We have multiple openings for Applied Statistics Researcher. You will engage in cutting edge research design and deployment of statistical methods to solve important decision and detection problems stemming from the Laboratorys core mission spaces. We invite you to join us if you have expertise in one of the following desired areas: Bayesian modeling uncertainty quantification analysis and design of computer experiments statistical learning statistical methods for Big Data or general statistical consulting. This position is in the Computational Engineering Division (CED) within the Engineering Directorate.

This position will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional responsibilities (outlined below) will be assigned if hired at the higher level.

In this role you will

• Contribute to and actively participate in research development and execution within one or more of the following areas: information retrieval and representation cyber security image and video analysis design of computer experiments climate modeling energy analysis computational biology lasers and optics.
• Design implement and analyze techniques in one or more of the above areas.
• Contribute to and actively participate with project scientists and engineers in scoping planning and formulating modeling/simulation efforts for physical engineering and computational systems in the areas of cyber security biological and environmental threat detection uncertainty quantification and others.
• Develop implement validate and document specialized analysis software tools and models as required.
• Collaborate and communicate with others in a multidisciplinary team environment including industrial and academic partners project managers and external sponsors to deliver results and accomplish research goals.
• Organize analyze and publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings.
• Perform other duties as assigned.

Additional job responsibilities at the SES.3 level

• Provide technical leadership and guidance to project teams developing state of the art methods and applying research results to meet programmatic goals while balancing priorities of customers and partners to ensure deadlines are met.
• Serve as the primary technical point of contact for program managers internally and at sponsor and partner organizations.
• Utilize advanced knowledge to provide  recommendations on methodologies and to influence deliverables to best meet sponsor needs.
• Mentor and advise LLNL scientists and engineers in applied statistics best practices.

Qualifications :

• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Masters degree in Statistics or other related technical field or the equivalent combination of education and related experience.
• Comprehensive knowledge and experience using programming skills in at least one prototyping language R/Matlab/Python as well as one of C/C/Java to enable high performance statistical computation.
• Experience developing and applying advanced statistical/machine learning models and algorithms for one or more of the following settings: classification clustering anomaly detection density estimation pattern recognition knowledge discovery.
• Experience developing independent research projects either through previous work experience or as demonstrated through publication of peer-reviewed literature.
• Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.
• Demonstrated initiative effective interpersonal skills and ability to work in a collaborative multidisciplinary team environment.
• Ability and desire to obtain substantial domain knowledge in fields of application and ability to communicate effectively with subject matter experts.

Additional qualifications at the SES.3 level

• Advanced knowledge and significant experience in developing and applying advanced statistical/machine learning models and algorithms for one or more of the following settings: classification clustering anomaly detection density estimation pattern recognition knowledge discovery.
• Significant experience executing independent research projects including experience leading interdisciplinary teams setting clear expectations delegating responsibilities and ensuring successful timely completion of objectives.
• Ability to adjust and dynamically reprioritize tasks in response to stakeholder input.

Qualifications We Desire

• PhD in Statistics or other related technical field or the equivalent combination of education and related experience.
• Familiarity with algebraic statistics and statistical models for combinatorial/algebraic structures.
• Experience with human language technology data mining and self-supervised learning.

Additional Information :

#LI-Hybrid

Position Information

This is a Career Indefinite position open to Lab employees and external candidates.

Why Lawrence Livermore National Laboratory

• Included in 2025 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visit  Clearance

  This position requires a Department of Energy (DOE) Q-level clearance.  If you are selected we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship. 

  Pre-Employment Drug Test

  External applicant(s) selected for this position must pass a post-offer pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

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  Remote Work :

  No

  
  

  Employment Type :

  Full-time