Data Science Engineer

Join us and make YOUR mark on the World! Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.  Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact. We have multiple openings for a  Data Science Engineer with a background in applied machine learning and data science for cybersecurity and power systems applications. You will design, build, and deploy novel data science capabilities to enhance the reliability and adversarial resilience of critical infrastructure. You will write code, create analytical tools and visualizations, diagnose complex systems, and discover innovative approaches to challenging problems. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate, in support of Global Security’s Energy and Homeland Security (E) program. Depending on your assignment, these positions may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week. 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. You will Design, develop, and apply machine learning and data science algorithms, including deep learning and modern AI techniques such as neural networks, transformers, and generative models, to analyze cybersecurity and power systems data. Analyze data and build analytical capabilities to improve the reliability and adversarial resilience of critical infrastructure. Write code to implement and deploy data science solutions and analytical tools, create visualizations, and follow software engineering best practices for code quality, testing, and documentation. Collaborate with multidisciplinary teams including cybersecurity experts, power systems engineers, and computer scientists. Support building research prototypes and capabilities for critical infrastructure protection, contributing to the development of new methodologies and tools. Provide solutions to moderately complex to complex data analytics challenges in the cybersecurity and power systems domains, using established and innovative methods. Perform other duties as assigned. Additional job responsibilities, at the SES.3 level Lead highly complex projects with technical and analytic challenges, developing innovative solutions and building advanced capabilities. Discover and pioneer new approaches to data science problems, pushing the boundaries of current methodologies, and transforming ideas from concepts to operational solutions. Present technical work and results to sponsors and technical audiences on a regular basis, demonstrating capabilities through hands-on demonstrations and deep technical discussions. Contribute to technical direction and strategy for data science capabilities in critical infrastructure protection by building proof-of-concept systems, demonstrating new approaches, and contributing ideas to research proposals. Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship. Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field, or the equivalent combination of education and related experience. Broad experience with Python programming and software development. Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems. Intermediate knowledge of software engineering best practices including version control, unit testing, and documentation. Proficient verbal and written communication skills necessary to collaborate within a team environment and present technical information to varied audiences. Effective interpersonal skills and initiative necessary to interact with all levels of personnel and work independently in a collaborative, multidisciplinary team environment. Demonstrated ability to balance multiple projects and prioritize competing demands while maintaining high-quality standards for deliverables. Additional qualifications at the SES.3 level  Advanced experience in applied machine learning and data science with demonstrated ability to deliver complex technical solutions independently. Advanced experience building innovative data science systems and discovering novel approaches to complex problems. Experience presenting technical work and demonstrations to both technical and non-technical audiences, including sponsors and stakeholders. Qualifications We Desire Master’s degree or PhD in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field. Experience with modern machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, and/or similar tools. Experience with deep learning techniques, transformer models, retrieval-augmented generation (RAG), fine-tuning pre-trained models, or adapting foundation models for specific application domains. Knowledge of cybersecurity principles and practices, including threat detection, anomaly detection, or security analytics. Experience with power systems, SCADA systems, industrial control systems, or operational technology environments. Experience with data visualization and effectively communicating analytical results to diverse audiences. Pay Range $146,340 - $222,564 Annually $146,340 - $185,544 Annually for the SES.2 level $175,530 - $222,564 Annually for the SES.3 level This is the lowest to highest salary we in good faith believe we woul