Applied Statistics Research Staff Member

Company Description

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are dedicated to fostering a culture that values individuals, talents, partnerships, ideas, experiences, and different perspectives, recognizing their importance to the continued success of the Laboratory’s mission.

Pay Range

$140,700 - $214,032

$140,700 - $178,392 Annually for the SES.2 level

$168,780 - $214,032 Annually for the SES.3 level

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Job Description

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 Laboratory's 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.
• Master’s 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 https://www.llnl.gov/inclusion/our-values

Security 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.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

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To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

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