DATA SCIENTIST ENGINEER

Company Details

CS Group is a major actor in the design, integration and operation of mission critical systems in Defense & Security, Space, Aeronautics and Energy sectors.

DESCRIPTION OF THE OFFER

Do you want to work in a company with a human dimension that encourages innovation, curiosity and taking responsibility?

Let your talent express itself in high-flying missions and share our human values ​​which promote the development of all, within a structured and agile organization recognized for its strong technical expertise in the service of exciting and rare projects on the market.

We invite you to join the Aeronautics, Energy and Industrial Systems Business Unit made up of 500 employees across France, we contribute to the development of programs in the sectors of scientific and technical information systems , digital simulation as well as systems sure .

To strengthen our project teams at one of our customers, we seek a (an) engineer (e) Data Scientist M / F .

You will work within the framework of Data engineering for applications in the aeronautical and space field.

Your role will be to analyze and characterize existing data, to apply learning algorithms on pre-processed data, and to perform automatic processing of Natural Language.

PROFILE REQUIRED

At CS GROUP, it is both your expertise and your personality that will make the difference:

  • You have good knowledge of Python, Docker, Machine learning and natural language.
  • You are rigorous, attentive and have a sense of pedagogy.

Don’t wait any longer, share your CV and let’s add our talents!

The sequence of events :

  • Our team of Recruiters process your application upon receipt.
  • Good news ! This interests us: we will contact you for a first telephone exchange. If this is positive, an operational manager will take over with a technical interview. Finally, you will meet one of our Recruiters during an HR interview. At the end of these meetings, we undertake to provide you with feedback within a maximum of 2 weeks.

Tagged as: analyze and characterize data

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