Data Scientist I
Company: PingWind
Location: Remote (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-09-29
About this role
Required Clearance: Secret
Required Education: Bachelor’s Degree
Required Experience: Minimum of 1 year of experience
Position Description
PingWind is seeking a Data Scientist I who will provide technical, analytical, and lifecycle support to the Maritime Electronic Warfare Systems Division (MEWSD) for critical U.S. Navy Electromagnetic Warfare (EW), Decoy, and Surface Electronic Warfare Improvement Program (SEWIP) systems. This role supports cradle-to-grave activities, including engineering, technology transition, installation, logistics, product support, test and evaluation, sustainment, maintenance, and repair. The Data Scientist I will integrate logistics, data science, reliability and maintainability engineering, and operations research to analyze and model complex systems, improve operational availability, and support data-driven decisions. This position directly contributes to optimizing warfighting capability, system readiness, reliability, and lifecycle performance while balancing mission requirements, performance, and cost.
Responsibilities
Typical Responsibilities/Tasks:
• Develop and implement analytical techniques and applications that transform raw data into meaningful, actionable information supporting operational and program decision-making.
• Apply data mining, data modeling, statistical analysis, natural language processing (NLP), and machine learning techniques to analyze large structured and unstructured datasets.
• Use data-oriented programming languages and analytical tools to collect, process, integrate, analyze, and interpret complex datasets.
• Develop data models and algorithms to identify trends, patterns, relationships, anomalies, risks, and performance indicators.
• Create effective data visualizations, dashboards, and dynamic reports that communicate complex analytical findings to technical and non-technical stakeholders.
• Interpret analytical results and provide data-driven fin...