ExxonMobil

ExxonMobil is a global leader in energy and petrochemical products, known for its complex supply chains and cutting-edge technology.

As a Mathematical Optimization and Data Science (MODS) intern, I contributed to ExxonMobil's efforts to optimize its extensive operations. My role involved developing mathematical models to solve large-scale optimization problems within the company's supply chain to enhance decision-making processes.

I was responsible for improving long-term portfolio valuation models for ExxonMobil's LNG business. My key contributions included reformulating and preprocessing the Long Term Portfolio Model, and enhancing performance without compromising quality. I converted an existing 3-stage Linear Programming (LP) solution into a 1-stage Mixed Integer Linear Programming (MILP) model, which improved its performance and interpretability. Additionally, I built a CPU parallelization framework to simultaneously evaluate multiple pricing forecasts, further enhancing the performance of the solution.