Message > CIFRE PhD in Machine learning applied to Merchandising

  • Forum 'Emplois' - Sujet créé le 12/10/2017 par Amadeus HR (1567 vues)

Le 12/10/2017 par Amadeus HR :

Today, with technology getting smarter by the minute, the future of travel has never been more exciting. With us, you won’t just be shaping your own career. You’ll be shaping the way the world moves.

Amadeus powers travel. Our solutions connect travelers to the journeys they want through travel agents, search engines, tour operators, airlines, airports, hotels, cars and railways. Our business success relies on our people being passionate in better technology that makes better journeys.

With us, you will work in an exciting and multicultural environment where you will be able to learn every day, drive your career, and enjoy your life at work - and out of work.



The Amadeus airlines division designs and develops highly reliable, first class and innovative IT solutions for airlines.
In the past decades, airlines’ Revenue Management Systems (RMS) focused mainly on optimising prices for seats. Airlines have started to sell ancillary services (e.g. bags, special seats or meals, wi-fi). The ex-tended content makes airlines decisions more complex:

? Recommender systems: what ancillaries to propose to the customer
? Pricing: pricing of the offer (seat and ancillaries).
? Presentation: how the offers should be presented (e.g. ranking)
? Personalisation: targeting an offer to an individual customer (e.g. discounts).

Today, RMS objective is thought to optimise the revenue for airline seats alone, while Merchandising’s objective is to expand the shopping basket (by offering up-sell, cross-sell, and ancillary services to the customer). Limited attention is paid to providing personalised offers, hence more relevant offers.
We believe the current approach is inadequate. We envision a future where our technology will be the central brain responsible for optimising offer creation, selection, pricing, and personalisation of decisions; the key to profitability is to merge RMS and Merchandising.
Technology has evolved, making airlines capable of collecting tremendous amounts of data; run experiments (e.g. A/B) from inspiration (search, shopping) to post flight (rating, social media).
The objective is to build intelligent systems that will leverage on both classical optimisation methodology and recent progress in Machine Learning.


  • Engineer degree or Master degree in computer science
  • First experience in artificial intelligence and machine learning
  • First experience in a research environment
  • Good programming skills in Scala & Python
  • Fluent in English

Start date: Last quarter 2017

Attractive package


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