Stage : Internship: Ticketing Data Mining and Clustering Tool (42661)
Site internet: http://www.amadeus.com
Internship: Ticketing Data Mining and Clustering Tool (42661)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.
Duration: 6 months: internship
The Storage team of the Ticketing R&D Department is in charge of the creation, consistency and integrity in database of millions of electronic tickets that passengers around the globe emit every day ! Our application is part of the mission-critical reservation system of Amadeus, used by almost 300 airlines and thousands of (office or online) travel agencies over more than 126 countries. Flight tickets being the main source of revenues for our customers, the team is directly involved in the money flow between all travel players (passengers, travel agents, airlines). This is what makes the team’s responsibilities both challenging and motivating!
The Ticketing R&D Department includes teams in Nice, Boston, Sydney and Bangalore. Its primary mission is to deliver the best Electronic Ticketing server in the world, allowing airlines and travel agencies to confidently entrust their travel documents to Amadeus.
The goal of the internship is to participate in building a Data Forensics web application that will detect, analyse and categorize the potential inconsistencies of the data stored in database, ideally before they induce significant incidents to our customers. This will tremendously help the teams’ investigations!
This tool will provide a fine monitoring of the database size trend over the time and most importantly an automatic clustering of the identified issues though machine learning and pattern recognition techniques .
· Requirement collection and problem statement
· Design and implementation of the Data mining & clustering algorithm (Python, SQL)
· Web portal development (Python, Django, Kibana)
· Testing and feedback integration
A successful candidate will need these skills:
· Passionate about software engineering
· Data mining, pattern recognition, machine learning
· SQL and Oracle
· Python (web servers is a plus)
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