Naval Reliability & Sustainment Data Scientist Port Hueneme, CAJob Description:JSL Technologies is seeking a
Naval Reliability & Sustainment Data Scientist to deliver advanced RAM-C analytics, predictive maintenance modeling, and supportability engineering for U.S. Navy surface combat systems and weapons programs. Operating directly at the Port Hueneme Division (PHD NSWC) government site, you will leverage fleet maintenance data, statistical analysis, and machine learning models to identify system failure trends, optimize readiness metrics (MTBF, MTTR, MLDT), and directly influence naval acquisition and sustainment decisions.
Primary Responsibilities:- RAM-C & Fleet Analytics: Extract, clean, and analyze readiness, maintenance, and operational data across Navy platforms using tools like Python, Tableau, and Advana Jupiter.
- Failure Analysis & Predictive Modeling: Identify systemic failure modes and root causes using statistical methods and Machine Learning (ML). Develop predictive models to improve material availability ($A_m$) and operational readiness ($A_o$).
- Reliability Engineering: Develop and update Reliability Block Diagrams (RBDs), Fault Tree Analyses (FTAs), FMECAs, Level of Repair Analyses (LORAs), and sparing models.
- Metrics & Reporting: Track key performance indicators-including Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR), and Mean Logistics Delay Time (MLDT)-and deliver weekly/monthly executive dashboards and technical reports.
- Design & Acquisition Support: Participate in system design and engineering reviews to evaluate new technologies and concepts of operation for long-term sustainment impacts.
- Stakeholder Coordination: Collaborate with In-Service Engineering Agents (ISEAs), OEMs, program sponsors, and fleet maintenance crews to resolve systemic RAM-C deficiencies.
- Data & Issue Tracking: Use Jira and custom workflows to document data engineering pipelines, track issue resolution, and report metrics to Navy leadership.
Requirements
Minimum Qualifications:- Work Authorization: Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future.
- Security Clearance: Ability to obtain and maintain an active U.S. DoD Secret clearance.
- Location: Must work on-site at the Naval Surface Warfare Center Port Hueneme Division (PHD NSWC).
- Data & Analytics Skills: Proven experience working with complex maintenance, logistics, or engineering datasets using analytics platforms.
- Core Engineering Knowledge: Understanding of RAM-C principles, root-cause analysis (RCA), and lifecycle supportability concepts.
- Communication: Ability to distill complex datasets into clear briefings, technical reports, and actionable recommendations for program leads.
Preferred Qualifications:- Navy/DoD Experience: Prior support for Navy combat systems, surface ships, or ISEA operations.
- Tech Stack: Proficiency in Python (pandas, scikit-learn, numpy), Tableau visualization, Jira, and DoD enterprise data platforms like Advana / Jupiter.
- Advanced Reliability Methods: Direct experience creating FMECAs, LORAs, Fault Trees, and spare parts optimization models.
- Agile/ML: Hands-on application of predictive maintenance analytics or Agile development frameworks in defense environments.
Security Clearance:Applicants must have an active security clearance and/or the ability to obtain and maintain a US Government Security Clearance. Selected candidates will be subject to a government security investigation and must meet eligibility requirements to obtain a DoD Government-granted security clearance. Individuals will be subject to a background investigation to include but not limited to, criminal history, employment and education verification, drug testing, and creditworthiness.
Salary Description
$75,000-$100,000 Yearly
