Advanced analytics and, where appropriate, AI/ML techniques (e.g., forecasting, anomaly detection, natural language processing of maintenance narratives) are used to identify readiness drivers and constraints, improve predictive analytics, and inform trade-space decisions that balance near-term readiness with longer-term capability objectives, including Fleet legacy platform/systems sustainment and modernization transitions. Working knowledge of the training of Naval Aviation maintenance and supply processes and their data systems (i.e., NAMP, P-485, OOMA/DECKPLATE, AMSRR, RSUPPLY, AFAST, ACES, TFMMS, SHARP/MSHARP, PSILS, and ASM).