Principal Enterprise Analytics & Operations Research Analyst

Principal Enterprise Schedule Analytics & Operations Research Analyst

Peraton is seeking a Principal Enterprise Schedule Analytics & Operations Research Analyst to support mission‑critical aviation programs aligned with the National Airspace System. The position serves as the lead analytical resource supporting enterprise schedule intelligence, operations research, optimization, and decision analytics for complex FAA modernization programs.

On‑site in Herndon, VA.

The role combines advanced schedule analytics, operations research, statistical analysis, predictive modeling, and enterprise studies to transform large volumes of schedule and program data into actionable recommendations. This is not a traditional scheduling position; it is a decision‑analytics role focused on improving enterprise execution.

• Analyze enterprise Integrated Master Schedules containing hundreds of thousands to millions of activities.
• Assess schedule health using critical path, total float, free float, logic density, open‑end analysis, constraints, baseline variance, and schedule integrity metrics.
• Identify missing predecessors/successors, out‑of‑sequence progress, resource conflicts, hidden dependencies, and enterprise schedule risks.
• Perform trend analysis, milestone forecasting, and cross‑program dependency assessments.

• Develop optimized courses of action (COAs) to improve enterprise schedule performance.
• Perform what‑if analyses, trade studies, predictive modeling, simulation, and sensitivity analyses.
• Quantify impacts of proposed schedule changes before implementation.
• Develop recovery strategies and recommend optimal sequencing of work.

• Conduct independent studies assessing vendor production capacity, raw material availability, manufacturing throughput, installation sequencing, workforce utilization, resource constraints, and supply chain impacts.
• Evaluate enterprise business rules and cross‑program impacts.
• Support strategic planning through quantitative and qualitative analysis.

• Develop, refine, and optimize analytical queries within the IRIS platform.
• Build reusable query templates and analytical models.
• Validate, cleanse, and integrate schedule, cost, logistics, production, and performance data.
• Leverage AI‑enabled analytics and knowledge graph capabilities to identify hidden scheduling constraints.

• Develop executive dashboards, visualizations, decision packages, and analytical briefings.
• Translate complex technical findings into concise recommendations for executive leadership.
• Support executive governance boards, FAA integration sessions, and program reviews.

• Partner with program managers, schedulers, systems engineers, risk managers, logistics personnel, and government stakeholders.
• Support enterprise solutioning efforts to identify and resolve schedule friction points.

• U.S. citizenship required.
• Must have ability to obtain / maintain a Public Trust clearance.
• Bachelor’s degree with 8 years of experience or Master’s degree with 6 years of experience.
• Degree in Operations Research, Systems Engineering, Industrial Engineering, Data Science, Mathematics, Statistics, Computer Science, Business Analytics, Engineering, or related STEM discipline.
• Experience supporting large, complex government, aerospace, or defense programs.
• Experience analyzing Integrated Master Schedules using Primavera P6 or equivalent scheduling tools.
• Experience with statistical analysis, optimization, predictive analytics, simulation, or operations research.
• Experience developing executive‑level briefings and decision support products.
• Strong analytical thinking, written communication, and presentation skills.

• Exposure to FAA programs or NAS systems.
• Experience with FAA systems, federal modernization efforts, or mission‑critical environments.
• Master’s degree in Operations Research, Systems Engineering, Industrial Engineering, or Data Analytics.
• FAA, DoD, or federal modernization program experience.
• Experience with SQL, Python, R, Power BI, Tableau, Acumen Fuse, Acumen Risk, Safran Risk, or similar analytical platforms.
• Knowledge of DCMA 14‑Point Assessment, IPMDAR, MIL‑STD‑881, and schedule risk methodologies.
• Experience with AI‑enabled analytics, digital engineering, and knowledge graph technologies.
• PMP, PMI‑SP, AACE, INCOSE, or equivalent professional certification.