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Internship: Automatic error analysis using machine learning algorithmsJoin 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 Revenue Accounting Department is in charge of developing state of art revenue accounting solutions for airlines. Contrary to traditional batch oriented revenue accounting systems requiring intensive manual labor, Amadeus solution consists on integrated online applications, focusing on increasingly productivity and automation.
You'll be joining the accounting team, in charge of one of the core and most vital components of this product. Analyzing customer needs, proposing innovative technical solutions and delivering robust software are among the team main responsibilities. As central component, cooperation with other teams and traversal functional and technical awareness is part of the team main qualities.
Error analysis is one of the most resource intensive tasks in the Revenue Accounting application. When a document such as a flight ticket cannot be properly processed, several root causes may lay behind. To name a few, configuration issues, software bugs and application input are some of the reasons preventing the correct document processing.
The current workflow for investigating these issues is semi-automatic. When investigating a set of documents in error, analysts try to identify problem categories and their corresponding matching criteria (pattern). These criteria are manually codded by software developers so that each document may be assigned to one category.
The purpose of this internship is help the team topropose and implement a solution allowing the automation of the pattern discovery step, using machine learning techniques. The intern will participate in following activities:
· Survey of state of art machine learning algorithms and the libraries implementing them;
· Analysis of the current error investigation workflow in order to identify the most appropriate technique to be used. The following is suggested as a starting trail (but is in no way the sole possible direction):
· Unsupervised machine learning such as data clustering;
· Supervised machine learning such as data classification;
· Implementation of a platform capable to process the documents in error. It should allow an agile validation and fine tuning of the hypotheses taken in such way that if one technique shows to be ineffective, trying another technique is trivial;
· Validation of the results, including performance (time to analyze the data), accuracy and usefulness of the patterns discovered.
If time permits, the intern will help th team to address one or more follow-ups:
· Integration of the platform into the current investigation workflow;
· Implementation of a graphic interface simplifying the interaction between analysts and the tool
· Suggestions of their own
Human: motivation, self-learning abilities
Computer: high-level and low-level language programming. The candidate should be proficient in a language having already a mature machine learning library available, such as Python, Java or Scala. Implementing the algorithms from scratch is out of scope of this internship.
Distinguishers: fluency in machine learning algorithms.
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