Advanced degree (Master’s or PhD) in Operations Research, Mathematics, Statistics, or a related quantitative field Solid theoretical foundation in RM: demand modeling, dynamic pricing, and network revenue management. Applied experience with RM or pricing tech solutions in transportation, travel, hospitality, retail, or a comparable domain is a big plus. Engineering and data craft Strong hands-on Python (including NumPy, Polars, Pandas, SciPy) and comfort with SQL on large datasets. Production-code experience is welcome but not required; what we expect is genuine interest in writing, reviewing, and maintaining code that runs reliably in production. Excellent communication: you explain complex quantitative concepts or optimisation trade-offs to technical and non-technical, commercial audiences alike, and you enjoy educating and advocating for sound RM solutions. Senior judgment: you scope your own work, balance short-term fixes with long-term direction, and respect the constraints of an existing system.

Work closely with commercial stakeholders to translate business requirements into well-scoped projects and respond to operational inquiries. Translate revenue management theory and industry best practices into concrete, testable improvements, from idea and experimentation through to production rollout. Co-own the evolution of the entire system through regular collaboration and discussions with peers across your team and neighboring engineering teams. Contribute to the technical health, reliability, and observability of the existing system.