Cybersecurity Data Scientist

Lawrence Livermore National Laboratory
Livermore, CA 94550
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We have an opening for a Cybersecurity Data Scientist with a background in machine learning for cybersecurity applications. You will contribute, provide subject matter knowledge, and contribute to research projects in the area of cybersecurity for critical infrastructure systems and civilian networks. This position is programmatically in Global Security's E Program and administratively will report to the Global Security Computing Applications Division (GS-CAD) within the Computing Directorate.

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

  • Research, develop, design and implement machine learning algorithms for cyber threat detection in operational technology environments, under limited direction.
  • Identify data types that should be collected in Operational Technology (OT) environments to enable detection of cyber events.
  • Test and validate developed algorithms on real OT data.
  • Identify, define, and scope moderately complex data analytics problems in the cybersecurity domain.
  • Develop cross-domain strategies for increased network security and resiliency of critical infrastructure, working with researchers in other disciplines.
  • Perform other duties as assigned.

Additional responsibilities at the SES.3 Level

  • Lead multidisciplinary teams in the areas of modeling and simulation for critical infrastructure cyber security, information security, and network security, while continuing to build LLNL's machine learning and data analytics capabilities.
  • Pursue program development opportunities by co-authoring proposals and proposing ideas that will address sponsor needs as well as identifying growth opportunities for existing customers that show an understanding of the customer space and needs.
  • Present results, provide subject matter knowledge and experience across multi-discipline projects, and engage with sponsors on a regular basis.

  • Master's degree in Computer Science, Computer Engineering, or a related field, or the equivalent combination of education and related experience.
  • Experience developing software in Python, C++, or C.
  • Broad experience implementing a deep learning workflow using one or more of the following frameworks: Theano, Tensorflow, Pytorch, or Keras.
  • Fundamental knowledge in and/or experience applying algorithms in one or more of the following Machine Learning areas: anomaly detection, one/few-shot learning, deep learning, unsupervised feature learning, ensemble methods, probabilistic graphical models, and/or reinforcement learning.
  • Broad knowledge of network protocols, such as DNS, or HTTPS.
  • Knowledge of and/or experience with computer vulnerabilities, such as, buffer overflows, code injection, format string, etc.
  • Ability to effectively manage concurrent technical tasks with conflicting priorities, as well as the ability to approach difficult problems with enthusiasm and creativity to change focus when necessary.
  • Ability to communicate comprehensive knowledge effectively across multi-disciplinary teams and to non-cyber experts, as well as demonstrate the proficient interpersonal skills necessary to effectively collaborate in a team environment.

Additional qualifications at the SES.3 Level

  • Significant experience leading multidisciplinary teams in the areas of machine learning and/or deep learning algorithms.
  • Significant experience pursuing program development opportunities by co-authoring proposals and proposing ideas that will address sponsor needs, as well as identifying growth opportunities for existing customers that show an understanding of the customer space and needs.
  • Experience presenting results, providing subject matter guidance across multi-discipline projects, and engaging with sponsors on a regular basis.

Qualifications We Desire

  • Ph.D. degree in Computer Science, Computer Engineering, or a related field.
  • Experience with high performance computing, parallel programing, and/or cloud computing, as well as experience with Modbus, DNP3, IEC 104, or IEC 61850 protocols, with a full-stack software development familiarity.
  • Knowledge of and/or experience with the reverse engineering process, using tools such as OllyDbg, IDA, or WinDbg with knowledge of the following source code analysis representations: abstract syntax tree, control flow graphs, and/or data dependency graphs.

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.

Security Clearance

LLNL is a Department of Energy (DOE) and National Nuclear Security Administration (NNSA) Laboratory. Some positions will require a DOE L or Q clearance (please reference Security Clearance requirement above). If you are selected and a clearance is required, 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. 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.

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.


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 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.

"},"jobDescription":{"title":"Job Description","text":"

We have an opening for a Cybersecurity Data Scientist with a background in machine learning for cybersecurity applications. You will contribute, provide subject matter knowledge, and contribute to research projects in the area of cybersecurity for critical infrastructure systems and civilian networks. This position is programmatically in Global Security's E Program and administratively will report to the Global Security Computing Applications Division (GS-CAD) within the Computing Directorate.

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

  • Research, develop, design and implement machine learning algorithms for cyber threat detection in operational technology environments, under limited direction.
  • Identify data types that should be collected in Operational Technology (OT) environments to enable detection of cyber events.
  • Test and validate developed algorithms on real OT data.
  • Identify, define, and scope moderately complex data analytics problems in the cybersecurity domain.
  • Develop cross-domain strategies for increased network security and resiliency of critical infrastructure, working with researchers in other disciplines.
  • Perform other duties as assigned.

Additional responsibilities at the SES.3 Level

  • Lead multidisciplinary teams in the areas of modeling and simulation for critical infrastructure cyber security, information security, and network security, while continuing to build LLNL's machine learning and data analytics capabilities.
  • Pursue program development opportunities by co-authoring proposals and proposing ideas that will address sponsor needs as well as identifying growth opportunities for existing customers that show an understanding of the customer space and needs.
  • Present results, provide subject matter knowledge and experience across multi-discipline projects, and engage with sponsors on a regular basis.
"},"qualifications":{"title":"Qualifications","text":"
  • Master's degree in Computer Science, Computer Engineering, or a related field, or the equivalent combination of education and related experience.
  • Experience developing software in Python, C++, or C.
  • Broad experience implementing a deep learning workflow using one or more of the following frameworks: Theano, Tensorflow, Pytorch, or Keras.
  • Fundamental knowledge in and/or experience applying algorithms in one or more of the following Machine Learning areas: anomaly detection, one/few-shot learning, deep learning, unsupervised feature learning, ensemble methods, probabilistic graphical models, and/or reinforcement learning.
  • Broad knowledge of network protocols, such as DNS, or HTTPS.
  • Knowledge of and/or experience with computer vulnerabilities, such as, buffer overflows, code injection, format string, etc.
  • Ability to effectively manage concurrent technical tasks with conflicting priorities, as well as the ability to approach difficult problems with enthusiasm and creativity to change focus when necessary.
  • Ability to communicate comprehensive knowledge effectively across multi-disciplinary teams and to non-cyber experts, as well as demonstrate the proficient interpersonal skills necessary to effectively collaborate in a team environment.

Additional qualifications at the SES.3 Level

  • Significant experience leading multidisciplinary teams in the areas of machine learning and/or deep learning algorithms.
  • Significant experience pursuing program development opportunities by co-authoring proposals and proposing ideas that will address sponsor needs, as well as identifying growth opportunities for existing customers that show an understanding of the customer space and needs.
  • Experience presenting results, providing subject matter guidance across multi-discipline projects, and engaging with sponsors on a regular basis.

Qualifications We Desire

  • Ph.D. degree in Computer Science, Computer Engineering, or a related field.
  • Experience with high performance computing, parallel programing, and/or cloud computing, as well as experience with Modbus, DNP3, IEC 104, or IEC 61850 protocols, with a full-stack software development familiarity.
  • Knowledge of and/or experience with the reverse engineering process, using tools such as OllyDbg, IDA, or WinDbg with knowledge of the following source code analysis representations: abstract syntax tree, control flow graphs, and/or data dependency graphs.

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Cybersecurity Data Scientist

Lawrence Livermore National Laboratory
Livermore, CA 94550

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Data Scientist
1st2019 - Data Scientist
Overall Rating: 1/199
Median Salary: $114,520

Work Environment
Very Good
4/220
Stress
Very Low
42/220
Growth
Very Good
33/220