Senior Operations Research Scientist

Job Description - Senior Operations Research Scientist (17178)

Job Description

Senior Operations Research Scientist ( 17178 )

Description

Senior Operations Research Scientist

INTRO

We are easy

Jet – a FTSE listed, £multi-billion low-cost airline that serves tens of millions of customers every single year. If you’re reading this, you have probably already been an easy

Jet customer, and you’ll know that there is no more iconic (or Orange!) travel brand in Europe.

We fly more than 1,207 routes, connecting 38 countries across Europe, and employ more than 18,000 colleagues. We’re on a mission to make low-cost travel easy – and whatever your role here, you’ll connect millions of people to what they love using Europe’s best airline network, great value fares, and friendly service.

What makes us easy

Jet? Our Promise Behaviours - we are Safe, Bold, Welcoming and Challenging. Four Behaviours. One Spirit. One easy

Jet.

READ ON IF YOU

• Have significant experience delivering operations research and optimisation solutions within complex operational environments.
• Enjoy solving large-scale routing, scheduling, capacity planning and resource allocation challenges using advanced mathematical modelling.
• Are passionate about translating complex business challenges into innovative, data-driven solutions that create measurable business value.
• Have expertise in optimisation, simulation, stochastic modelling and algorithm development.
• Can be in our fantastic Luton head office 3 x per week.

THE TEAM

As part of our Data Science and Advanced Analytics capability, the Operations Research team partners with colleagues across Operations, Planning, Crew and Engineering to tackle some of the most complex challenges in aviation. The team delivers optimisation, simulation and decision-support solutions that drive operational excellence, resilience and efficiency across easy

Jet's network.

THE ROLE

As a Senior Operations Research Scientist, you will lead the design, development and deployment of mission-critical optimisation models, simulation tools and decision-support solutions that support key operational decisions across the airline. You will combine deep technical expertise with strong stakeholder engagement to solve complex operational challenges, influence strategic decisions and deliver measurable business impact.

Key responsibilities include:

• Leading the architecture and delivery of advanced operations research solutions across crew planning, aircraft scheduling, network resilience and ground operations.
• Designing and implementing high-performance optimisation algorithms and production-grade solutions using Python, C++ and commercial optimisation solvers.
• Integrating optimisation, simulation and reinforcement learning techniques to solve complex multi-stage decision problems.
• Partnering with senior stakeholders to translate business challenges into mathematical models with clear operational and commercial outcomes.
• Leading delivery across the full data science and optimisation lifecycle, from opportunity identification through to deployment and continuous improvement.
• Collaborating with data and technology teams to ensure data quality and availability for optimisation solutions.
• Mentoring colleagues in operations research techniques, conducting technical reviews and helping establish best practice across the organisation.
• Representing easy
  
  Jet through industry events, academic partnerships and engagement with the wider optimisation community.

Requirements of the Role

WHAT WE'RE LOOKING FOR

• Expert knowledge of operations research, mathematical programming, simulation methodologies, stochastic processes and decision theory.
• Advanced programming skills in Python and C++, or similar high-performance languages.
• Strong experience using optimisation software such as Gurobi, CPLEX or Xpress.
• A proven track record of delivering operations research and optimisation solutions within operational environments.
• Experience solving large-scale routing, scheduling or resource allocation problems within aviation, transport, logistics, supply chain or other complex network-based environments.
• Strong understanding of algorithm design, computational complexity and…