Applied Statistics Researcher

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

$168,780 - $256,824 Annually

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

$202,500 - $256,824 Annually at the SES.4 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 an 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. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate.

These positions will be filled at either level based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level.

In this role, you will

• Conduct research, development, post-processing, and documentation of results in 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 utilize in-depth analysis techniques in one or more of the above areas.
• Collaborate with project scientists and engineers and actively contribute to the scope, planning, and formulating modeling/simulation efforts for complex 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 with others in a multidisciplinary team environment, including industrial and academic partners, to accomplish research goals, solve complex technical challenges, as well as develop innovative methods and/or technologies.
• Organize, analyze, document, author, and publish research results in peer-reviewed scientific or technical journals and present and explain results at external conferences seminars and/or technical meetings.
• Lead technical teams in executing complex projects and tasks while balancing priorities of customers and partners to ensure deadlines are met. Provide technical guidance, and mentor and coach team members as needed.
• Serve as point of contact for program managers internally and at sponsor and partner organizations.Perform other duties as assigned.
• Perform other duties as assigned.

Additional job responsibilities, at the SES.4 level

• Serve as a subject matter expert in highly advanced concepts, providing strategic technical advice to internal senior management and external sponsors.
• Represent LLNL as the primary technical contact on external scientific or technical committees.
• Work independently to establish project vision and strategy, influence technical direction and decisions, and drive successful project outcomes.
• Lead and guide teams and direct highly advanced technical tasks to deliver critical project components, while ensuring alignment with project schedules and budgets.

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 relevant technical discipline, or the equivalent combination of education and related experience.
• Advanced level knowledge of, and significant 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.
• Advanced level knowledge of, and significant experience in researching, designing, and applying statistical methods, statistical/machine learning models, and algorithms to solve complex decision and detection problems in one or more of the following settings: classification, clustering, anomaly detection, density estimation, pattern recognition, knowledge discovery.
• Significant experience directing, leading, developing, and executing independent research projects as demonstrated through publication of peer-reviewed literature.
• Advanced organizational, verbal and written communication, and interpersonal skills to collaborate effectively in a multidisciplinary team environment, and with subject matter experts, including authoring reports, presenting, and explaining complex technical information.
• Demonstrated ability to exercise independent judgment in determining optimal techniques and methods.

Additional qualifications at the SES.4 level

• Significant experience developing innovative solutions and methods requiring in-depth analysis of multiple highly complex factors.
• Significant leadership experience in directing technical projects and managing and mentoring multidisciplinary teams.
• Expert communication skills to effectively advise and influence senior management and external sponsors, and to interact with stakeholders and decision-makers.

Qualifications We Desire

• PhD in Statistics or relevant technical discipline.
• Familiarity with algebraic statistics and statistical models for combinatorial/algebraic structures.
• Experience with human language technology, data mining, and self-supervised learning.
• Ability and desire to obtain substantial domain knowledge in fields of application.

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.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

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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