Resume

Sabre Corporation, Labs Division

Technical lead for B2B revenue management products used by airline clients, owning end-to-end design across data pipelines, machine learning models, and optimization components
Lead clarity and diagnostic strategy for complex pricing systems, building explainability frameworks and tools that make model behavior transparent to technical and commercial stakeholders
Partner closely with sales and client teams to translate decision science into clear, defensible product narratives that accelerate adoption and improve solution credibility
Act as project lead across cross-functional teams, coordinating delivery, technical direction, and stakeholder communication while mentoring junior engineers and scientists

The Walt Disney Company

Led technical design and development of a large-scale dynamic pricing system for Disney parks, spanning optimization, simulation, and production deployment
Modeled complex RM problems using MIP, stochastic, nonlinear, and nonconvex programming, balancing model fidelity with operational constraints
Acted as clarity owner in cross-functional forums—translating science into actionable narratives for product, operations, and leadership
Coordinated intern cohorts and mentored scientists on priorities, timelines, and delivery practices

Alexandria, Virginia

Developed land cover classification and atmospheric correction algorithms using scikit-learn
Created reusable Python tools to address common geospatial analysis problems
Contributed to internal ML knowledge-sharing through presentations and workshops

Clemson University

Taught undergraduate business & engineering statistics (STAT 2300 & 3090) to classes of 100+ students
Designed custom assessments and lectures tailored to curriculum needs
Developed and published new state-of-the-art large scale, convex optimization solving algorithms as part of Ph.D. studies in applied mathematics

Clemson University

Clemson University