Many large organizations want to develop data science capabilities, but the traditional complexity and legacy of such companies don’t allow a fast and agile evolution toward data-driven decision making. EasyJet is working toward becoming completely data driven. Alberto Rey shares real-world examples on how easyJet is tackling the challenges of scaling up its analytics capabilities.
With more than 450,000 flights a year and close to 80 million passengers, easyJet has considerable experience in data-driven decision making. The airline collects large amounts of data on operations, engineering, consumer preferences, and pricing trends to increase the efficiency of its operations and deliver a better product at a lower cost to its customers, relying on its team of analysts and data scientists to solve heterogeneous business problems.
Alberto Rey is head of data science at easyJet, where he leads easyJet’s efforts to adopt advance analytics within different areas of the business. Alberto’s background is in air transport and economics, and he has more than 15 years’ experience in the air travel industry. Alberto started his career in advanced analytics as a member of the Pricing and Revenue Management team at easyJet, working in the development of one of the most advanced pricing engines within the industry, where his team pioneered the implementation of machine-learning techniques to drive pricing. He holds an MSc in data mining and an MBA from Cranfield University.
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