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Data Scientist - Entry Level

Entry Level | Full-time
Information Technology/Computing | livermore, CA | 03/17/2023

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Company Description

Join us and make YOUR mark on the World!

Are you passionate about data science? Do you enjoy staying updated on the latest methods and developing solutions to novel data science problems? Are you interested in joining some of the brightest talent in the world to create solutions with national impact that advance our scientific fields and 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 committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory’s mission.

Pay Range

$103,290 - $139,128 Annually for the SES.1 level
$123,960 - $166,992Annually for the SES.2 level

Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay including education, experience, the external labor market, and internal equity.

Job Description

We have openings for Data Scientists to provide solutions for various projects. You will work in a dynamic, multidisciplinary team of independent/entrepreneurial computer scientists, engineers, and scientific staff who research, develop, and integrate state-of-the-art algorithms, software, hardware, and computer systems solutions to challenging research and development problems. These positions are in the Global Security Computing Applications Division (GS-CAD) within the Computing Directorate.

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

In this role you will

  • Collaborate with scientists and researchers in one or more of the following areas: data intensive applications, natural language processing, graph analysis, machine learning, statistical learning, information visualization, low-level data management, data integration, data streaming, scientific data mining, data fusion, massive-scale knowledge fusion using semantic graphs, database technology, programming models for scalable parallel computing, application performance modeling and analysis, scalable tool development, novel architectures (e.g., FPGAs, GPUs and embedded systems), and HPC architecture simulation and evaluation.
  • Work with other LLNL scientists and application developers to bring research results to practical use in LLNL programs.
  • Assess the requirements for data sciences research from LLNL programs and external government sponsors.
  • Carry out development of data analysis algorithms to address program and sponsor data sciences requirements.
  • Engage other developers frequently to share relevant knowledge, opinions, and recommendations, working to fulfill deliverables as a team.
  • Contribute to technical solutions, participate as a member of a multidisciplinary team to analyze sponsor requirements and designs, and implement software and perform analyses to address these requirements.
  • Develop and integrate components-such as web-based user interfaces, access control mechanisms, and commercial indexing products-for creating an operational information and knowledge discovery system.
  • Perform other duties as assigned.

Additional job responsibilities, at the SES.2 level

  • Contribute to multiple parallel tasks and priorities of customers and partners, ensuring deadlines are met.
  • Solve abstract problems, converting them into useable algorithms and software modules.
  • Provide solutions that require analysis of multiple factors and the creative use of established methods.


  • Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
  • Bachelor’s degree in data science, computer science, mathematics, statistics, or related field, or the equivalent combination of education and related experience.
  • Fundamental knowledge of one or more of the following: scientific data analysis, statistical analysis, knowledge discovery, supervised learning, unsupervised learning, deep learning, reinforcement learning, natural language processing, and big data technologies.
  • Skilled in all aspects of the data science life cycle:  feasibility / background research, data exploration, feature engineering, modeling, visualization, deployment
  • Fundamental experience developing data science algorithms with C++, Python, or R in Linux, UNIX, Windows environments, sufficient to integrate solutions into larger applications.
  • Experience with scikit-learn, PyTorch, TensorFlow, or similar machine learning (AI/ML) development API for the purpose of developing data science solutions.
  • Ability to effectively handle concurrent technical tasks with conflicting priorities, to approach difficult problems with enthusiasm and creativity and to change focus when necessary, and to work independently and implement research concepts in a multi-disciplinary team environment, where commitments and deadlines are important to project success.
  • Sufficient interpersonal skills necessary to interact with all levels of personnel.
  • Sufficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.

Additional qualifications, at the SES.2 level

  • Effective analytical, problem-solving, and decision-making skills to develop creative solutions to complex problems.
  • Broad experience with one or more of the following technical languages, concepts, or constructs: Python, scientific data analysis, statistical analysis, knowledge discovery, supervised learning, unsupervised learning, deep learning, reinforcement learning, natural language processing, and big data technologies.
  • Proficient experience with at least one of the following advanced ML concepts: Transfer Learning, distributed ML (data/model), ML operations, generative models, Bayesian optimization, computer vision modeling, transformers, graph neural networks, uncertainty quantification, surrogate modeling, or techniques for data-poor ML (low-shot, coresets, etc).

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

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

Why Lawrence Livermore National Laboratory?

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.

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.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

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

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.

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