Apprenticeship/ Internship: Alternative flight guidance during disruption using machine learning

Description de l'offre

Join us and shape the future of travel

Shaping the future of travel has always been important to us at Amadeus. Today, with technology getting smarter by the minute, that future is more exciting than ever.

We work at the heart of the global travel industry. Amadeus offers you the opportunity to learn and grow and drive your own progression in an exciting and multicultural environment.

Our people are driven by a passion for 'Where next?' If you want to shape your career and the future of travel, Amadeus is the place for you.

Team Description

Amadeus is a world leader in providing IT solutions for the whole travel industry. It provides a comprehensive set of products for managing airline business from reservation to operational systems managing passengers and aircrafts at the airport.

You will be integrated in the team that is in charge of the passenger disruption, finding alternative travel solutions for passengers impacted by schedule changes.

Main Responsibilities

This internship/ apprenticeshipaims at providing decision support to agents choosing alternative flights when performing a re-accommodation. Indeed, it is very common that agents decide to override the alternative flights selected by the automatic process or override parameters/settings. Also, the passengers often reject the default proposal and choose another alternative more suitable for them.

This is why we would like to provide the agents guidance on their choices by showing historical aggregated data on similar problems with identified patterns.

The intern/ apprenticewill participate in following activities:

· Develop a tool to:
· Analyze bookings impacted by the re-accommodation process, highlighting how many times the choice made by the process was changed by the passenger afterwards
· Based on machine learning, identify similar situations from the historical data
· Predict solutions that passengers are likely to prefer with corresponding statistics and integrate the information in the re-accommodation software, when the user chooses the alternative solutions. “For instance, if you choose this alternative flight, you have 60% chance that the booking will be modified after”

Requirements

Data analysis, Python, angular, machine learning

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