Sustainment Data Science & Analysis Support

Sustainment Data Science & Analysis Support San Diego, CA

About Us:

JSL Technologies, Inc. (JSL) is a certified Small Disadvantaged Business (SDB) and Veteran-Owned government contractor delivering engineering, logistics, and program support services to the Department of Defense (DoD). Our team of more than 200 professionals is dedicated to providing practical, innovative, and cost-effective solutions that support critical missions.

Headquartered in Oxnard, California, JSL supports government customers across the nation. We foster a culture built on integrity, collaboration, and accountability, empowering our employees to perform at a high level and continuously improve the way we serve our customers.

At JSL, our people are the foundation of our success. We offer competitive compensation and a comprehensive benefits package that supports the well-being and professional growth of our team.

JSL Technologies is seeking an entry-level Data Scientist to support Navy engineering and sustainment programs through Python-based data analysis, automation, visualization, and analytical tool development. This position is well suited for a recent college graduate with strong Python programming skills and an interest in applying data science techniques to equipment reliability, maintenance, readiness, and sustainment challenges. Prior Navy, Reliability, Availability, Maintainability, and Cost (RAM-C), logistics, or sustainment experience is not required.

The selected candidate will receive exposure to Navy systems, data sources, analytical processes, and reliability terminology while working with experienced engineering and logistics personnel at the Government facility in San Diego, California.

• Develop, maintain, and improve Python scripts used to collect, clean, organize, validate, and analyze engineering, maintenance, logistics, readiness, and operational data.
• Work with structured and unstructured datasets to identify trends, patterns, anomalies, and data-quality issues.
• Automate repetitive data-processing, reporting, and visualization activities using Python and related analytical libraries.
• Support the development of dashboards, charts, reports, and other data products used by engineering and program stakeholders.
• Apply statistical analysis, machine learning, predictive analytics, or other data-science methods under the guidance of senior technical personnel.
• Assist experienced engineers and analysts in evaluating reliability, availability, maintainability, cost, readiness, and sustainment data.
• Support senior engineers and analysts in developing and evaluating RAM-C and supportability products, including reliability models, failure analyses, repair-level analyses, sparing analyses, and readiness metrics. Prior experience with these products is not required.
• Support the preparation of technical reports, readiness summaries, recurring status reports, and presentation materials.
• Document data sources, analytical methods, assumptions, code, and results so analyses are understandable and repeatable.
• Collaborate with engineers, logisticians, maintenance personnel, program personnel, and other stakeholders to understand analytical requirements.
• Learn and use Government-provided systems and tools, which may include Advana Jupiter, JIRA, Tableau, and Navy maintenance or readiness databases.
• Become familiar with RAM-C concepts and analytical products such as Failure Modes, Effects and Criticality Analysis (FMECA), Level of Repair Analysis (LORA), Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR), Mean Logistics Delay Time (MLDT), and sparing analysis through on-the-job training.
• Participate in technical meetings and design reviews and provide data-analysis support as assigned.

• Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future.
• Ability to obtain and maintain a U.S. Government Secret security clearance.
• Bachelor's degree in Data Science, Computer Science, Software Engineering, Computer Engineering, Mathematics, Statistics, Operations Research, Engineering, or a closely related technical discipline.
• Academic, internship, research, project, or professional experience developing software or performing data analysis using Python.
• Strong understanding of Python programming fundamentals, including data structures, functions, object-oriented programming, debugging, and code documentation.
• Experience using common Python data-analysis libraries such as pandas, Num Py, Sci Py, scikit-learn, Matplotlib, or comparable libraries.
• Ability to clean, transform, analyze, and visualize data from multiple sources.
• Basic understanding of statistics, data modeling, machine learning, or predictive analytics.
• Ability to communicate analytical results clearly through written reports, visualizations, and presentations.
• Ability to learn unfamiliar engineering, reliability, logistics, and Navy terminology.
• Ability to work collaboratively with…