Data scientist for Future Project Office (m/f)

Description de l'offre

Data scientist for Future Project Office (m/f)

Airbus Toulouse

Airbus is a global leader in aeronautics, space and related services. In 2017, it generated revenues of € 67 billion and employed a workforce of around 130,000. Airbus offers the most comprehensive range of passenger airliners from 100 to more than 600 seats. Airbus is also a European leader providing tanker, combat, transport and mission aircraft, as well as Europe's number one space enterprise and the world's second largest space business. In helicopters, Airbus provides the most efficient civil and military rotorcraft solutions worldwide.

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

A vacancy for a Data scientist for Future Project Office has arisen within Airbus (Commercial Aircraft) in Toulouse. You will join Future Project Office within Engineering department.

Are you passionate about aircraft design?

Do you have another passion for data analytics and are eager to combine the two to bring added value to the next generation of Airbus products?

Then this position is for you!

The position lies within the Future Project Office, an Airbus Engineering Domain with teams located all across Europe (France, UK, Germany and Spain). Although Toulouse-based, this role will offer you the opportunity to work in a transnational & multi-functional environment in close collaboration with other entities from Design Office, Manufacturing, Digital transformation, R&T, etc.

Airbus Future Projects Office mission is to lead the preliminary definition of next aircraft, from incremental developments to "clean sheet" design, in collaboration with the various disciplines of Design Office and other relevant stakeholders. This mission requires remaining upfront of new technologies, new technics, new methodologies and new ways of working.

Profil recherché

Tasks & accountabilities

Within this team, your mission will be to propose, contribute and lead in a "pioneering mind-set" the exploitation of disparate big datasets with main objective to bring knowledge back to a/c preliminary design. Datasets are for instance about:

·  Operational data: confronting actual aircraft usage in-service versus design objectives
·  Flight tests data: enhancing understanding of aircraft behaviour
·  Disciplines datasets: aero, structure, loads, for improved modelling
·  Market data so to weight design objectives by their impact and set attractive targets
·  Manufacturing datasets to be linked with cost estimations methods

These activities will enable to discover new potential, synergies or margins to update design rules and to link it to new technologies for the benefit of future aircraft design.

With same approach, you will be asked to contribute to transverse activities so to improve knowledge management through internal forums extracts (inference engine, chatbots,...), numerical methods enhancement, ...

Required skills

Your boarding pass:

·  Proficiency of R-programming and/or scientific Python or equivalent
·  Experience with relational database management (e.g. SQL).
·  Experience of data science studies involving data gathering/crawling, data cleaning, data processing/analysis and visualization
·  Degree in Aerospace Engineering/Mechanical Engineering or similar
·  Open mind-set and curiosity for new technologies (incl. digital ones) & ways of working
·  Good ability to act as a “team player” and easy communication in a transnational and multidisciplinary environment
·  Autonomy
·  Language Skills: negotiation level of English

Your plus:

·  Good knowledge of distributed / cluster computing frameworks: Spark (PySpark, SparkR), Hadoop, (Amazon Cloud?).
·  Good knowledge of Machine Learning
·  Ability to generate surrogate models