Job Description & Details
This role puts you at the core of heavy-duty revenue management and pricing optimization across massive entertainment, media, and park ecosystems. If you like tackling complex mathematical models that directly influence multi-million dollar business strategies, this contract is worth your time.
What You'll Actually Be Doing
You will spend your days developing, testing, and deploying advanced decision science models that handle yield management, forecasting, and pricing puzzles. You'll act as an internal consultant, bridging the gap between raw data and executive decision-making. Expect to dive into data mining, build custom simulation techniques, and present your findings directly to business partners who want to see clear, profitable outcomes.
The Core Tech Stack
You need a rock-solid foundation in optimization techniques like mixed-integer, nonlinear, or stochastic optimization, paired with strong programming chops in Python, Java, or R. Because you will be building state-of-the-art algorithms and simulation tools from scratch, your code needs to be clean, scalable, and ready to translate complex academic research into production-ready enterprise solutions.
Interview Expectations
Expect the hiring team to present you with a blank-slate optimization problem—such as pricing a perishable inventory resource under uncertainty—and ask you to sketch out a mathematical formulation on the spot. They are looking to see how you break down ambiguity, choose between deterministic versus stochastic models, and justify your computational approach. Be ready for deep-dive technical grilling on your past ML or operations research projects.
Application Advice
Your resume needs to scream Operations Research and Advanced Analytics to clear the recruiter screening. Make sure explicit keywords like mixed-integer optimization, discrete-event simulation, revenue management, and Python or R are prominently featured in your project descriptions. If you have a Master's or Ph.D. thesis or practical industry experience dealing with demand forecasting and resource allocation, put that right at the top.