Commercial Data Scientist / Data Analyst
easyJet Commercial Analytics
We are easyJet – a FTSE-250 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 easyJet 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 easyJet? Our Promise Behaviours – we are Safe, Bold, Welcoming and Challenging. Four Behaviours. One Spirit. One easyJet.
The Opportunity
Join easyJet's Commercial Analytics team and shape the future of revenue management at scale. We're building next-generation pricing and optimisation systems that directly drive business performance across the airline industry. You'll work at the intersection of data science, business strategy, and software engineering—developing algorithms that impact real commercial decisions every single day.
Our Revenue Management and Commercial Data Science chapter is responsible for powering pricing, network planning, scheduling, and inflight retail optimisation. We're currently reimagining our entire platform, modernizing the backend, redesigning the UI, and enhancing our algorithms to meet tomorrow's commercial challenges.
What You'll Do
- Design and develop advanced algorithmic models for dynamic pricing strategies, revenue forecasting, and cost optimisation
- Test rigorously through simulations, backtests, shadow testing, and A/B experiments to quantify real-world impact
- Conduct research on airline commercial problems and emerging industry dynamics
- Translate insights into action by presenting findings and recommendations to business stakeholders and subject matter experts
- Build sustainably by maintaining robust code, comprehensive documentation, and scalable systems
- Run and maintain existing systems, ensuring optimal performance, reliability, and continuous operational improvement
- Collaborate cross-functionally with Trading, Network, Scheduling, Proposition, and Inflight Retail teams to implement integrated solutions
About Our Team
We're a diverse team of engineers, economists, statisticians, mathematicians, and computer scientists—all united by a passion for solving complex commercial problems with data and algorithms.
We leverage cutting-edge techniques in data analysis, machine learning, and optimisation to build systems that automate decision-making and drive competitive advantage. If you thrive in intellectually challenging environments and want your work to have immediate business impact, you'll fit right in.
What We're Looking For
Essential Qualifications:
- Degree in statistics, data science, econometrics, quantitative economics, operations research, mathematics, or related field
- 2+ years of experience in commercial analytics, algorithm development, or applied statistical/machine learning modelling
- Proficiency in SQL and Python
- Strong understanding of commercial/pricing problems and business fundamentals
- Advanced data skills: statistical modelling, machine learning, time-series forecasting, demand prediction, optimisation, inventory management
- Experience with dynamic pricing, stochastic processes, or Bayesian inference is a plus
Preferred Experience:
- Background in pricing, forecasting or optimisation roles within airlines, hospitality, car rentals, e-commerce, or similar dynamic pricing industries
- Familiarity with data engineering concepts (pipelines, data quality, testing, sampling)
Who You Are:
- Commercially minded with genuine curiosity about business problems, not just algorithms
- Comfortable working in a fast-paced, evolving environment
- Committed to continuous learning and iterative improvement
- Excellent communicator who can translate technical concepts for business audiences
- Data-driven problem solver with strong analytical rigor
Why Join Us?
- Work on real, high-impact systems used by thousands of flights daily
- Access to world-class data and complex, real-world optimisation challenges
- Collaborate with leading minds across data science, engineering, and commerce
- Develop in-house expertise with tools built specifically for airline problems
- Be part of a team that values both technical excellence and business acumen
“Please note that this role does not meet the criteria for visa sponsorship, and we are therefore unable to consider applicants who require sponsorship to work in the UK.”
How to Apply:
If you are a self-starter who can identify opportunities to drive greater success for the team and have a track record of building strong relationships with internal stakeholders, we would love to hear from you. Apply now to join our dynamic team!
What you’ll get in return:
At easyJet, we pride ourselves on a vibrant and inclusive workplace culture that supports and rewards innovation and excellence.
We offer:
- Competitive base salary
- Up to 20% annual bonus potential.
- 25 days holiday, pension scheme, life assurance, and a flexible benefits package.
- Discounted staff travel scheme for friends and family
- Annual credit for discount on easyJet holidays
- ‘Work Away’ scheme, allowing you to work abroad for 30 days a year
- Electric vehicle lease salary sacrifice scheme
Location & Hours of Work
We operate a hybrid working policy of 2 days a week spent with colleagues.
We look forward to your application and the possibility of you flying high with our team!
Application Process:
Interested candidates should apply through our careers portal.
Reasonable Adjustments:
At easyJet, we are dedicated to fostering an inclusive workplace that reflects the diverse customers we serve across Europe. We welcome candidates from all backgrounds. If you require specific adjustments or support during the application or recruitment process, such as extra time for assessments or accessible interview locations, please contact us at [email protected].
