Case Study: easyJet achieves IT–Data Science alignment with Domino Data Lab

How easyJet Bridges the Gap Between IT and Data Science

easyJet, the UK-based low-cost airline, faced drastic demand shifts during the COVID-19 pandemic that forced more frequent schedule changes and a rapid expansion of predictive analytics, automation, and real‑time learning. At the same time, friction between IT and data science—around access to infrastructure, tooling, and governance—threatened to slow innovation and operational responsiveness.

Ben Dias led a pragmatic approach to close that gap: clearly explain why controls are needed, adopt a Lean Startup model that progressively tightens governance as projects move toward production, and reuse existing IT processes while adding model monitoring. The result has been faster, safer deployment of models, greater use of automation, external data, and reinforcement learning, and improved collaboration that helps easyJet respond to demand shifts and advance its data‑driven strategy.

easyJet

Ben Dias

Director of Data Science and Analytics