Internship / Data analytics for product safety (m/f)

Description de l'offre

Internship / Data analytics for product safety (m/f)

Airbus Blagnac

Airbus Group is a global leader in aeronautics, space and related services. In 2015, the Group - comprising Airbus, Airbus Defence and Space and Airbus Helicopters - generated revenues of € 64.5 billion and employed a workforce of around 136,600.

Our people work with passion and determination to make the world a more connected, safer and smarter place. Taking pride in our work, we draw on each other's expertise and experience to achieve excellence. Our diversity and teamwork culture propel us to accomplish the extraordinary - on the ground, in the sky and in space.

Description of the job

Airbus Blagnac is looking for an intern for a 6-month internship.

Within the Product Safety Enhancement department, you will contribute to develop and implement data analytics techniques to further enhance descriptive and predictive safety capabilities.

This internship will start on 2nd January 2017 (subject to some flexibility).

Internships at Airbus Group

Profil recherché

Tasks & accountabilities

Your main mission will include:

·  Working closely with aviation safety specialists and data specialists (flight tests, design office) to understand data model and define relevant data and parameters to consider,
·  Fusing the different data sources if needed,
·  Elaborating the operational definition of the events to detect / monitor and identify precursors,
·  Mining the data to investigate and potentially discover new use of the provided data for safety,
·  Specifying and then generating derived parameters from the raw data,
·  Applying appropriate statistical methods and algorithms (e.g. machine learning) to analyse the selected data and generate safety insights,
·  Using appropriate data visualisation means to provide actionable results to product safety control room.

Required skills

You are studying a Bac+5 degree / Master degree or equivalent in aerospace engineering with a major in data science or an equivalent degree in applied mathematics.

You ideally have initial experience in the domain and you have a good knowledge:

·  Statistics & machine learning,
·  Computer programming (R/Python, etc.),
·  Relational and non-relational database system,
·  Distributed computing & associated environment,
·  HBASE system files.

A knowledge or previous experience in applying machine learning techniques for outlier detection and classification would be preferable (Bayesian network, Classification trees, one-class SVM, etc.).

You are data curious and highly autonomous to perform technical activities.
You are a strong team player and have excellent interpersonal skills.

English: advanced to negotiation level,
French: negotiation level.