Message > Offre de stage chez Amadeus: Artificial Intelligence for Hotels Recommendation

  • Forum 'Stages' - Sujet créé le 04/10/2017 par mboudia (103 vues)


Le 04/10/2017 par mboudia :

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

This internship will be hosted in the Innovation and Research Division of Amadeus, in the team dedicated to Analysis and Research. The scope of the team focuses on identifying business opportunities in the Travel Industry and improving existing business by introducing new approaches and technologies. The team competencies cover a large scope such as mathematical modeling and software prototyping in the fields of operational research and data science. 

Subject

Amadeus is the world leader in the travel industry supporting our customers at the different levels from strategic to operational areas. Amadeus distributes travel solutions through its Global Distribution System (GDS). The content sold through the GDS is diverse, including flight segments, hotel stays, cruises, car rental and airport-hotel transfers. Amadeus business concerns the delivery of appropriate travel solutions to travel retailers so that they can optimize the booking conversion from final customers. Therefore we need to design state-of-the-art recommendation engines capable of analysing historical bookings and automatically recommending the appropriate travel solutions.

During this internship, we propose to analyse the goldmine of Amadeus data and to design a prototype of a machine learning based recommender system for Hotels. Specifically, a prototype recommendation engine should select a subset of relevant hotels to be intelligently displayed so that the potential customer can perceive the value of the offers. The aim of the prototype would be to maximise conversion (i.e. the look-to-book ratio). Context of the request and the associated trip or customer characteristics are key assets to fine tune such an engine. Public data sources can be considered on top of Amadeus records, which might improve algorithm performances.

Big data technologies have been applied for hotel recommender systems for more than a decade. However, the Amadeus business context is novel due to the richness of available data sources (bookings, pictures, ratings, …) and the variety of distribution channels: indirect through travel agencies or direct (website, mobile, mailbox).

The internship will be organized as follow:

1-literature review, 2- data processing and cleaning, 3- define relevant key performance indicators, 4- implement and test recommendation models.

Required skills

Programming language: Any of Python, R or Java (nice to have: Hadoop, H2O, Spark)

Engineering specialization in one of the following: Data Science, Statistics, Machine Learning or Operational Research

Personal required skills

Curiosity

Team spirit

Good written and spoken English

 

Any duplication and display of partial or full content of our job advertisement on any support, such as brochures, websites, mail, emails, this list is not exhaustive, is strictly forbidden without prior formal Amadeus’ authorisation. 

Recruitment agencies: Amadeus does not accept agency resumes. Please do not forward resumes to our jobs alias, Amadeus employees or any other company location. Amadeus is not responsible for any fees related to unsolicited resumes.

Lien pour candidature

https://career012.successfactors.eu/career?career_ns=job_listing&company=AmadeusProd&navBarLevel=JOB_SEARCH&rcm_site_locale=en_GB&career_job_req_id=75889&selected_lang=en_GB&jobAlertController_jobAlertId=&jobAlertController_jobAlertName=&_s.crb=Yxutmvj3mDlK%2fqa%2bReBfuLOm4Og%3d

 







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