MAAR Analysis Airline Fleet Replacement

Brief

This project demonstrates computational financial modeling, operations research, and quantitative systems analysis through the development of a parametric airline fleet replacement model. I contributed to building structured datasets, implementing a Python based economic simulation framework, and analyzing purchase versus lease strategies using present worth and rate of return metrics. The model integrated fuel price regression, hedging strategies, labor and maintenance cost structures, depreciation modeling, and tax considerations to generate scalable, data-driven investment recommendations. This work highlights strengths in financial automation, structured documentation, economic decision modeling, and translating complex operational systems into computational tools for strategic planning.