Affordability Theory of Constraint (TOC) Engineer

About the Role

The Affordability Theory of Constraint (TOC) Engineer plays a key role in supporting Raytheon’s Discrete Event Simulation (DES) capability. This role focuses on learning and applying TOC-based simulation modeling to evaluate system behavior, identify constraints, and support critical program milestones. Collaboration with modelers and cross-functional teams is essential to develop accurate inputs and analyze simulation results that drive impactful decision-making.

This is an onsite role located in Tucson, AZ.

Key Responsibilities

• Prepare and load structured model inputs, including Excel and database-driven datasets.
• Assist modelers in running discrete event simulations to analyze throughput, queue behavior, cycle time variation, and resource utilization.
• Identify emerging constraints and evaluate their impact on production flows, supply chain interactions, and sustainment activities.
• Perform data preparation, cleansing, and validation for parameters such as yields, routing definitions, process times, resource availability, and demand signals.
• Document assumptions, data sources, and configuration changes to maintain traceability.
• Participate in sensitivity analyses, scenario comparisons, and parameter sweeps under the guidance of senior staff.
• Generate preliminary plots, tables, and summaries from simulation outputs to support internal reviews.
• Collaborate with Affordability Leads, Systems Engineering, Operations, and Supply Chain teams to understand model inputs and interpret findings.
• Contribute to continuous model updates to align with evolving program conditions.

Requirements & Tech Stack

• The ability to obtain and maintain a U.S. government issued security clearance is required.
• U.S. citizenship is required.
• DoD Clearance: Top Secret
• Active and existing security clearance required after day 1.
• Microsoft Excel
• Structured datasets

Qualifications

• Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and less than 2 years of prior experience unless prohibited by local laws/regulations.
• Experience using engineering or analytical principles through coursework, analysis methods (e.g., optimization, simulation, process modeling), or project experience.

Preferred Qualifications

• Exposure to simulation, modeling, statistics, or data-driven analysis through coursework or internship experience.
• Experience with tools such as Python, MATLAB, R, Power BI, Tableau, or JMP for basic data manipulation or visualization.
• Experience with basic manufacturing concepts such as cycle times, routing, resources, or yield behavior.
• Knowledge of systems engineering fundamentals or production/supply chain workflows.