Naval RAM-C Data Scientist: Predictive Maintenance

JSL TECHNOLOGIES INCORPORATED; Port Hueneme (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

JSL Technologies, Inc. in Port Hueneme, CA seeks a Naval Reliability & Sustainment Data Scientist to deliver RAM-C analytics, predictive maintenance modeling, and supportability engineering for Navy systems.

On-site at PHD NSWC, you will leverage maintenance data, statistics, and ML to identify failure trends and influence acquisition decisions. You will extract and analyze data, build predictive models, develop RAM-related engineering artifacts, and deliver dashboards to Navy leadership,

Qualifications

• Experience delivering RAM-C analytics for defense programs.
• Experience with predictive maintenance and reliability modeling.
• Ability to distill complex data into actionable recommendations for Navy leadership.

Responsibilities

• RAM-C & Fleet Analytics: extract, clean, analyze maintenance data across Navy platforms using Python/Tableau/Jira.
• Failure Analysis & Predictive Modeling: identify failure modes; develop models to improve readiness.
• Reliability Engineering: develop RBDs/FTAs/FMECAs/LORAs and sparing models.
• Metrics & Reporting: track MTBF/MTTR/MLDT and deliver dashboards/reports.
• Design & Acquisition Support: participate in system design reviews for sustainment impact.
• Stakeholder Coordination: work with ISEAs, OEMs, sponsors, and fleet crews.
• Data & Issue Tracking: use Jira to document pipelines and report metrics.

Skills

RAM-C analytics

Predictive maintenance

Data analysis

Statistical modeling

Communication

Tools

Python

Tableau

Jira

Advana/Jupiter

Job description

JSL Technologies, Inc. in Port Hueneme, CA seeks a Naval Reliability & Sustainment Data Scientist to deliver RAM-C analytics, predictive maintenance modeling, and supportability engineering for Navy systems.

On-site at PHD NSWC, you will leverage maintenance data, statistics, and ML to identify failure trends and influence acquisition decisions. You will extract and analyze data, build predictive models, develop RAM-related engineering artifacts, and deliver dashboards to Navy leadership,