Internship - Predict Paid Seats Bookability

Job description

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

Our business success relies on our people being always passionate about what we do. We believe in aiming for excellence, taking responsibility, working together and putting our customers first.

We encourage you to be part of new and exciting projects and for you to take the lead when it comes to your progression.

Since mobility allows you and Amadeus to grow, we always look internally first when searching for candidate.

Start:
January 2017 for 3 to 6 months

Context:

Amadeus is the leading provider of IT solutions to the worldwide travel and tourism industry. We are at the heart of exciting projects aiming to distribute ancillary services (e.g. paid seats) for North American carriers. In order to provide the best offer to our customers and to insure adoption of our product, we would like to extract patterns from our database in order to identify by who, when and how the product is used, and detect any error patterns leading to a lost of revenue for us and our partners.

Objective:

The objective of this internship is to extract patterns from our database in order to identify which type of users are booking paid seats, how and when they are booking it (how many days in advance, from which channel, etc.) and which are the flows and type of records with a high probability of rejection at seat booking or issuance.

Team Description

Our team is composed of software engineers and business analysts working in collaboration with our regional customers and product management team to deliver IT solutions for the American market. We are leading projects aiming to distribute the content of North American airlines (flights and services) to travel agencies using New Distribution Capability (NDC) standard. While overseeing the overall changes, our team is responsible for delivering the backend changes related to pricing and ticketing impacts.

Main Responsibilities

· Get relevant data set from our EMD (Electronic Miscellaneous Document), PNR (Passenger Name Record) and transactional databases.
· Categorize customers and cross reference the data set with static data such as type of office, Time of the day, Date before departure, geo mapping, etc.
· Work on feature detection to reduce the dimensionality of the model
· Apply several machine learning / pattern recognition techniques to learn from the data set and extract patterns
· Measure the accuracy of the models on real production environment
· Explain and document the considered options/algorithms, the reasons behind the chosen path, and the results obtained

Amadeus team will support the candidate in providing the domain expertise as necessary. The team would help evaluating the developed model, address the legal/security aspects attached to the project, provide guidance in the accessing the APIs and infrastructure.

Requirements

· Machine Learning knowledge
· Pattern recognition/Mathematical skills
· Programming skills
· Innovative thinker
· Able to express ideas and opinions clearly, both in oral and written format
· Ability to deliver design documents and basic presentations
· Proactive and positive attitude

The posting of vacancies and the treatment of applications are, in each Amadeus location, subject to national law and possible collective agreements with local staff representation. Internal Mobility policies vary from office to office, please check with your local HR representative the requirements and policy in place. E.g. a minimum time on position or Line Manager approval may be requested.