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Senior Cybersecurity Data Scientist
Information Technology/Computing | livermore, CA | 01/25/2021
Job Code: SES.4 Science & Engineering MTS 4 / SES.5 Science & Engineering MTS 5
Organization: Global Security
Position Type: Career Indefinite
Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: A job-related pre-placement medical examination may be required
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 looking for individuals that demonstrate an understanding of working in partnership with team peers, who engage, advocate, and contribute to building an inclusive culture, and provide expertise to solve challenging problems.
We have an opening for an experienced Computer Scientist with a background in machine learning for cybersecurity applications. You will provide subject matter expertise and leadership to research projects in cybersecurity for critical infrastructure systems and civilian networks. You will participate in strategy and business development for the Cyber and Infrastructure Resilience (CIR) program in the Global Security (GS) Principal Associate Directorate. This position is programmatically in GS’s E Program and administratively will report to the payroll supervisor of the hiring organization.
This position 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
- Lead and support a diverse range of advanced research projects requiring in-depth analysis and creative use of innovative methods in machine learning and data analytics for cyber threat detection in operational technology (OT) environments, partnering with senior management and organizations across the Laboratory.
- Responsible for ensuring growth of existing and development of new machine learning and data analytics capabilities at LLNL.
- Provide subject matter expertise in informing development of new algorithms and identifying data sets that can be used for cyber threat detection in OT environments.
- Identify new opportunities and applications of LLNL’s data analytics capabilities and help create vision and technical direction for existing work in the area under the consultative direction of leadership
- Develop new program growth opportunities through interaction with existing and potential sponsors and the development of research proposals.
- Identify, define and determine scope of highly complex data analytics problems in cybersecurity domain.
- Develop cross-domain strategies for increased network security and resiliency of critical infrastructure, partnering with researchers in other disciplines.
- Perform other duties as assigned.
Additional job responsibilities, at the SES.5 level
- Guide and provide scientific and technical direction for a portfolio of highly complex technical tasks and projects that consistently require the application of creativity and innovation; set broad research/project vision and strategy and influence technical direction for Laboratory, self and/or others wielding extensive influence with senior management and policy makes.
- Provide highly innovative solutions to abstract complex problems/ideas, convert them into useable algorithms/software modules, and provide solutions that require in-depth analysis of multiple factors and the creative use of established methods.
- Responsible for high-level goal setting, strategic planning, directing and accomplishing project/program goals and objectives significantly impacting major Laboratory programs and contributing to the revolutionary advancement of knowledge.
- Master’s degree in computer science, computer engineering, or related field or the equivalent combination of education and significant related experience.
- Expert experience in Python, C++, or C.
- Highly advanced experience implementing a deep learning workflow using one or more of the following frameworks: Theano, TensorFlow, PyTorch, or Keras.
- Subject matter expert experience in applying algorithms in one or more of the following Machine Learning areas: deep learning, unsupervised feature learning, ensemble methods, probabilistic graphical models.
- Significant experience or understanding of network protocols: DNS, HTTPS.
- Expert knowledge and/or experience of computer vulnerabilities, such as, buffer overflows, code injection, format string, etc.
- Demonstrated ability to effectively lead teams and create technical direction and vision, write research proposals and secure sponsor funding.
- Expert ability to communicate comprehensive knowledge effectively across multi-disciplinary teams and to non-cyber experts and proficient interpersonal skills necessary to effectively collaborate in a team environment.
Additional qualifications at the SES.5 level
- Expert knowledge of state-of-the-art technologies in machine learning and deep learning algorithms.
- Extensive experience and demonstrated ability to plan the integration and implementation of new programs and/or operational best practices.
- Extensive project leadership experience and demonstrated ability to apply, lead and develop cutting-edge principles and research, work independently while effectively managing concurrent technical tasks with competing priorities.
Qualifications We Desire
- PhD in computer science, computer engineering or related field.
- Significant experience in systems engineering, including practical experience in critical infrastructure cybersecurity. Knowledge of one or more of the following computer science disciplines: embedded systems, systems programming, software engineering, parallel programming and high performance computing. Significant experience with full-stack software development.
- Demonstrated ability to secure sponsor funding through winning proposals and sponsor relationships. Previous experience working Department of Energy, Department of Homeland Security, Department of Defense or utility company.
Why Lawrence Livermore National Laboratory?
- Included in 2020 Best Places to Work by Glassdoor!
- Work for a premier innovative national Laboratory
- Comprehensive Benefits Package
- Flexible schedules (*depending on project needs)
- Collaborative, creative, inclusive, and fun team environment
Learn more about our company, selection process, position types and security clearances by visiting our Career site.
LLNL is a Department of Energy (DOE) and National Nuclear Security Administration (NNSA) Laboratory. Most positions will require a DOE L or Q clearance (please reference Security Clearance requirement). 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. In addition, all L or Q cleared employees are subject to random drug testing. An L or Q clearance requires U.S. citizenship. If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted. For additional information please see DOE Order 472.2.
Equal Employment Opportunity
LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. 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.
If you need assistance and/or a reasonable accommodation during the application or the recruiting process, please submit a request via our online form.
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