Computational Automation and Data Science Scientist

The Extreme Light, Matter, and Fusion Directorate (LMF), formerly the NIF & Photon Science Directorate, is seeking a Computational Automation and Data Science Scientist to leverage AI to support the automation, optimization, and integration of manual computational procedures used in scientific research, engineering, and laboratory operations. The successful candidate will develop data-analysis algorithms, machine-learning applications, database interfaces, and automated workflows that improve efficiency, repeatability, and decision-making.
This position will work within an interdisciplinary research and development environment and collaborate with scientists, engineers, technicians, software developers, and industrial partners. The selected candidate will translate scientific and engineering requirements into computational tools, automate existing analysis processes, manage scientific data, and support assigned software, data, and computational capabilities.
In this role, you will
Review existing manual computational procedures and develop automated, scalable, and maintainable workflows under general direction. Work includes algorithms for data processing, feature extraction, classification, prediction, anomaly detection, and statistical analysis.
Apply established machine-learning methods to scientific, engineering, laboratory, or operational data, including designing, training, validating, and evaluating models using appropriate performance metrics.
Develop tools and scripts for data ingestion, cleaning, transformation, visualization, and analysis.
Interface with databases and data systems, including developing queries, data pipelines, schemas, and data-management solutions.
Integrate computational tools with laboratory instruments, engineering systems, software applications, and data repositories to create user-focused tools that improve the efficiency, consistency, and traceability of technical procedures.
Document, test, validate, and maintain automated workflows, analytical tools, and operating procedures, and prepare technical reports, experimental plans, and procedures.
Perform other duties as assigned.
Additional job responsibilities, at the SES.2 level
Assess data quality, uncertainty, bias, reproducibility, and limitations of computational results. Develop methods for identifying trends, correlations, outliers, anomalies, and failure conditions in complex datasets using creative and innovative approaches; and recommend improvements to methods and processes.
Contribute and maintain procedures for assigned computational, software, and data-analysis capabilities, including support for machine-vision or image-analysis methods, exploring a variety of approaches within established methods and contributing to the advancement of existing techniques.
Prepare patents and peer-reviewed publications; and in open and classified environments, both internally and externally; provide informal guidance and mentoring to less-experienced personnel. Work independently with minimal direction while contributing effectively to multidisciplinary research and development teams.
Ability to obtain and maintain a U.S. DOE Q-level security clearance, which requires U.S. citizenship.
Bachelor of Science degree in computer science, data science, computational science, mathematics, statistics, engineering, or a related field, or an equivalent combination of education and relevant experience.
Experience developing computational tools, scripts, algorithms, or automated workflows, including experience with data analysis, data processing, statistical methods, or scientific computing.
Experience using machine-learning techniques for classification, regression, clustering, anomaly detection, prediction, or related applications.
Experience with one or more programming languages commonly used for data analysis and automation, such as Python, MATLAB, R, C++, or a comparable language.
Familiarity with databases, data structures, data modeling, SQL, application programming interfaces, or data-management systems.
Sufficient verbal and written communication skills to collaborate effectively in a team environment, present and explain technical information, and learn and apply new computational methods, software tools, and technical concepts.
Additional qualifications, at the SES.2 level
Comprehensive knowledge of computational and data-science concepts, demonstrating full competency.
Relevant previous experience and demonstrated ability to perform independent work, including automating manual scientific, engineering, laboratory, or business processes.
Broad application of technical principles, theories, concepts, and techniques in an applicable scientific or engineering discipline, in addition to working knowledge of other related fields, such as software-development practices (version control, testing, code review, documentation, and continuous integration).
Experience establishing and maintaining procedures for computational, software, or data-analysis capabilities, and recommending process improvements as appropriate.
Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information, including preparing technical reports, publications, presentations, or software documentation.
Demonstrated ability to independently learn and apply new computational methods, software tools, and technical concepts, and to establish effective working relationships with multidisciplinary teams.
Qualifications We Desire
Master of Science degree in computer science, data science, computational science, mathematics, statistics, engineering, or a related field, or an equivalent combination of education and relevant experience.
Demonstrated experience automating manual scientific, engineering, laboratory, or business processes.
Experience designing, training, validating, deploying, and maintaining machine-learning models, including deep learning, neural networks, time-series analysis, computer vision, image processing, or natural-language processing.
Experience developing machine-vision systems or image-analysis algorithms.
Experience integrating software with laboratory instruments, sensors, robotic systems, or engineering tools.
Experience developing standard operating procedures, laboratory work instructions, computational workflows, software documentation, or data-management plans.
Experience with cloud computing, high-performance computing, containerization, or distributed data processing.
Experience with uncertainty quantification, experimental design, statistical modeling, or physics-informed machine learning, and ability to assess model performance, interpretability, robustness, generalizability, and operational limitations.
Experience with database design, SQL optimization, data warehousing, data lakes, or scientific data repositories; developing data pipelines, application programming interfaces, dashboards, or user-facing analytical tools; and a record of publications, patents, presentations, software products, or other technical contributions in computational science, data science, machine learning, automation, or a related field.
Pay Range
$121,830 - $185,544 Annually
$121,830 - $154,500 Annually for the SES.1 level
$146,340 - $185,544 Annually for the SES.2 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.

Skills
Python, C++, SQL, Machine Learning, Deep Learning, Data Analysis, Data Modeling, Computer Vision, MATLAB, Documentation

Employment type
Full-time

Work arrangement
No