Predictive Logistics Systems Engineer - Huntington Ingalls Industries

Key Responsibilities

• Develop and maintain predictive models that forecast logistics demand, inventory levels, and maintenance schedules across multi‑domain platforms.
• Collaborate with data scientists, operations analysts, and engineering teams to integrate sensor data and operational metrics into actionable insights.
• Design data pipelines and ETL processes using SQL and Python to ingest, clean, and transform large datasets for model training and deployment.
• Implement model validation, performance monitoring, and continuous improvement strategies to ensure high accuracy and reliability.
• Document model logic, assumptions, and results for cross‑functional stakeholders and support knowledge transfer to operations teams.

Requirements

• Mid‑level experience (Engineer 3) in predictive analytics or data science within a logistics or operations context.
• Proficiency in Python, SQL, and machine learning libraries (scikit‑learn, TensorFlow, PyTorch).
• Strong understanding of data modeling, feature engineering, and model deployment best practices.
• Experience with large‑scale data processing and performance optimization.
• Excellent communication skills and ability to translate technical findings into business recommendations.