System Analyst

Overview

The Maintenance and Site Services - Automation and Performance Technologies (MSS-APT) group integrates reliability engineering, predictive maintenance (PdM), building automation systems (BAS), and enterprise asset management (EAM) to drive operational excellence across Los Alamos National Laboratory. Among other things we enable the transition from time based to condition based maintenance through the intelligent use of data, sensors, and automation.

• Design, integrate, and support data pipelines between PdM sensors, BAS (Sky Spark), and EAM (Asset Suite) to enable condition-based maintenance and real-time fault detection.
• Collaborate with Reliability Engineers and BAS Engineers to configure and validate data collection, analytics, and alert systems.
• Develop and deploy AI and machine learning interfaces that automate equipment health diagnostics, trend recognition, and maintenance recommendations.
• Build system level dashboards and analytics in Sky Spark, Microstrategy, Power BI, or equivalent platforms for leadership and operational teams.
• Collaborate with institutional organizations and network engineers to ensure cyber secure, scalable data communication architectures.
• Develop technical documentation, data flow diagrams, and API interface specifications for system interoperability.
• Serve as a subject matter expert (SME) for integration between automation technologies, condition monitoring systems, and the CMMS.
• Lead feasibility studies and proof-of-concepts for new automation and AI technologies that enhance APT group capabilities.
• Provide mentoring and knowledge transfer to peers within Reliability Engineering, BAS, and CMMS disciplines.

Minimum

Job Requirements:

• Technical Integration & Systems Knowledge: Proven experience in integrating sensor-based systems with enterprise applications (e.g., EAM, BAS, or SCADA). Strong understanding of communication protocols (BACnet, Modbus, MQTT, OPC UA) and their use in building and industrial automation. Experience configuring or programming Sky Spark, Niagara, or similar analytics platforms. General knowledge of predictive maintenance systems, data acquisition, and vibration, temperature, and pressure sensor technologies.
  
  Familiarity with IT/OT network architectures, cybersecurity practices, and system reliability standards.
• Software & Data Development: Proficiency in scripting or programming (Python, JavaScript, SQL, or similar). Experience designing APIs and data integrations across diverse platforms. Ability to manage, clean, and visualize data across multiple databases and environments. Knowledge of AI/ML model deployment, including supervised learning, anomaly detection, or digital twin applications, preferred.
• Communication &
  
  Collaboration:
  
  Ability to translate complex technical concepts into practical, actionable insights for non-technical audiences. Demonstrated collaboration across multidisciplinary teams including engineering, IT, and operations. Strong problem-solving, documentation, and project coordination skills.
• Maintenance Operations Understanding: Familiarity with facility operations, asset management, and maintenance workflows. Ability to identify process improvement opportunities through automation and data analytics.
• Education/
  
  Experience:
  
  Position requires a Bachelor’s Degree in a relevant field and 8 years of related experience; or an equivalent combination of education and experience directly related to the occupation. At this level, post graduate course work may be expected.

Desired

Qualifications:

• Experience with Sky Spark, Asset Suite, or similar BAS/CMMS integration projects.
• Proficiency in AI/ML libraries (e.g., Tensor Flow, scikit-learn, PyTorch).
• Experience implementing condition-based monitoring or predictive analytics systems.
• Knowledge of data governance and data visualization tools such as Power BI, Grafana, Microstrategy, or Tableau.
• Experience developing logical, cohesive data views or models that improve the accessibility, consistency, and user-friendliness of reporting and analytics.
• Understanding of LANL network security requirements and DOE/NNSA IT standards.
• Active DOE Q Clearance (preferred, not required at time of hire).
• Degree in Engineering, Computer Science or a related field.
• Professional certification in Automation, AI or Reliability Engineering desired.

The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.

Regular appointment employees are required to serve a period of continuous service in their current position in order to be eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the time required, they may only apply for Laboratory jobs with the documented approval of their Division Leader. The position commitment for this position is 1 year.

• Please submit a detailed resume, along with a cover letter addressing how you meet the minimum…