Computer Scientist; Scientist

What You Will Do

This position is open for external candidates only to apply.

This position will be filled at either the Scientist 1 or 2 level, depending on the skills of the selected candidate. Additional job responsibilities (outlined below) will be assigned if the candidate is hired at the higher level.

Scientist 1 $ 96,600- $158,000

Scientist 2 $ 106,400- $176,000

Los Alamos National Laboratory is seeking a highly motivated Database Engineer/Computer Scientist to help modernize and transform surveillance and predictive analytics capabilities through scalable data infrastructure, advanced analytics, and AI-enabled technologies. This opportunity is well suited for candidates from industry, national laboratories, academia, government or other technical environments who are interested in applying their database and computer science expertise to mission-driven work.

• Support the design, development, and maintenance of database systems for engineering and surveillance data
• Develop, maintain, or improve data pipelines to ingest, clean, structure, validate, and integrate datasets from multiple sources
• Support AI/ML and advanced analytics applications by preparing, organizing, and improving datasets for predictive modeling, reporting, or analysis
• Assist with implementing efficient data storage, retrieval, and query solutions for technical datasets
• Collaborate with engineers, analysts, and scientists to develop integrated data solutions supporting predictive surveillance and system health monitoring
• Develop or maintain tools and workflows to correlate data across components, assemblies, and assets
• Support data integrity, security, accessibility, and long-term maintainability of database systems
• Support visualization, reporting, and analytical tools that enable actionable technical insight

Experience designing, developing, managing, or optimizing relational and/or non-relational database systems, including data modeling, schema design, query development, indexing, and performance tuning.

Proficiency with SQL and Python, with experience developing automated data pipelines, ETL/ELT workflows, data integration processes, or model-ready datasets.

Familiarity with AI/ML workflows, predictive analytics environments, feature engineering, or data preparation practices that support advanced modeling and analysis.

Experience working with large, complex, or heterogeneous technical datasets, including engineering, scientific, manufacturing, test, surveillance, or system health data.

Strong analytical, problem-solving, and communication skills, with the ability to work effectively in multidisciplinary technical teams across engineering, science, analytics, and software disciplines.

• Technical Leadership:
  Experience leading complex technical projects, guiding technical direction, and making independent decisions related to database architecture, data integration, or analytical infrastructure
• Advanced System Architecture:
  Experience designing scalable, reliable, secure, and maintainable data systems that integrate information across multiple sources
• Strategic Data Integration:
  Experience developing strategies to integrate diverse engineering, scientific, surveillance, or operational datasets in support of analytics, reporting, and decision-making
• Mentorship and Team Coordination:
  Experience mentoring staff, coordinating multidisciplinary technical teams, and communicating technical recommendations to leadership, customers, or stakeholders
• Innovation and Capability Development:
  Experience identifying, evaluating, and implementing data engineering tools, methods, or technologies that improve analytical capability, workflow efficiency, or mission outcomes

Position requires a Bachelor's d degree in a STEM field from an accredited college or university and 2 years of related experience, or an equivalent combination of education and experience directly related to the occupation.

Positions requires a Bachelor' degree in a STEM field from an accredited college and university and 4 years of related experience, typically with post-doctoral research experience at a university or national lab or equivalent experience directly related to the occupation.

• Experience in one or more of the following areas is especially valuable:
• Database platforms such as PostgreSQL, MySQL, MongoDB, Neo4j, or similar technologies
• Python data tools such as Pandas, Num Py, SQL Alchemy, PySpark, or related libraries
• Data modeling, schema design, indexing, performance tuning, and query optimization
• Cloud computing, distributed computing, or high-performance computing environments
• AI/ML data preparation, feature engineering, or model-ready dataset…