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Apprenticeship - Decision-making infrastructure in processing of airfare data contentJoin 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.
The mission of Data and Pricing Services (DPS) is to deliver accurate and consistent servicing for search, shopping and pricing engines thanks to efficient and scalable processing of travel content.
As part of the Data and Pricing Services department, the Fare Data Mining team is a cross-functional team in charge of analysing airfares and fare-related data processing flows. It particularly aims at developing cost models to leverage the fare construction capabilities.
Our greatest challenge is to support increasing trends in travel industry: always more airfares and complex restrictions defined by travel providers, larger search criteria and more diversified travel options offered to the end-users.
As member of the team, the apprentice will engage his/her analytical and programming skills in building innovative software modules and evaluating their improvements.S/He will contribute to the prototyping benchmarking and deployment of a new infrastructure aiming at helping our services continuously assess the optimal processing to minimize processing cost:
- Collect relevant data from various sources (fare database, production statistics, process KPI…)
- Analyse data and predict behaviours (from business expertise, machine-learning module…)
- Exploit results dynamically within data processing (activate/de-activate processes, changing order…)
Current internship and consultancy are exploring Hadoop/Hive and MongoDB on the collection side, R language and Weka on the analysis and exploitation side.
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