Senior Analyst
CurrentCurrently developing innovative machine learning algorithms to replace current weapon planner software in the Integrated Air and Missile Defense System- Developed scenarios and generated high-fidelity Monte Carlo missile performance data- Conducted comprehensive data analysis to determine and derive critical features- Designed classification and regression models to predict probability of hit-- Performed hyperparameter selection using cross-validated grid searching with different scoring functions-- Assessed model performance using various performance metrics, learning curves, and validation curves-- Mitigated imbalanced data issues using minority class scoring metrics and sampling techniquesDesigned and developed analysis software in Python/Qt. This tool enables the ability to conduct simultaneous analysis of tactical telemetry data, digital simulation data, and hardware-in-the-loop data. Support for complex analytical queries from large Monte Carlo datasets facilitate multi-venue statistical analyses and performance insights that were previously impossible. Determined pre-flight test probability of success and assess potential flight test risks through simulation analysis. Investigated anomalous behavior and determined the root cause of each failure. Identified software bugs through code inspection of the C/C++, FORTRAN, and Ada. Verified algorithmic correctness of critical subsystems such as guidance, autopilot, target state estimation, and seeker signal processing by deriving models from first principles and comparing to software implementation.