Ensemble | Landing AI models: what can we learn from easyJet?

On Wednesday 16 November, both online and in person in Manchester, we were joined by Ben Dias, Director of Data Science and Analytics at easyJet. Ben is currently leading the delivery of easyJet’s data strategy aimed at realizing the company’s ambition of becoming the world’s leading data-driven airline.

Session description:

It is both expensive and time-consuming to create models, but most of the AI models are eventually not delivered into production. Why is this so difficult? What are leaders and teams actually missing? How do they avoid the pitfalls? What are the practices and methods that will help get AI models into production quickly and effectively? Join the recording to hear how easyJet brings the key business and IT stakeholders into the project team in order to successfully accelerate and scale up the deployment of their AI models.

About the speaker:

Previously having worked at Royal Mail, Tesco and Unilever, Ben Dias has over 15 years’ industry experience in solving real-world problems in an industry setting. More recently, Ben has focussed on building and leading Data Science teams and applying the Lean Start-Up approach to Data Science within large organizations. He has experience in setting up and managing industrial research collaborations with academic and business partners. He is also actively engaged with the UK Mathematics community and very enthusiastic about inspiring the next generation of Mathematicians and Data professionals. Ben holds a PhD in Computer Vision and a Masters in Mathematics and Astronomy, both from UCL.