Senior Data Scientist

• The business need is understood and formalized in a descriptive datasheet or specifications
• The methods are identified through external researches and selected by their theoretical bases, advantages and drawbacks.
• The results of the analysis or the models are presented to the customers with data visualisation tools indicating the performances and the limits. The source code is delivered and explained if necessary.

• All stages of Machine learning project are implemented (pipeline, components, tests), respecting quality standards
• All valuable code is re-usabled by community
• Data Analysis models are monitored (technological watch) and partnerships are developed

• The metier is well supported by the data scientist network with proposals for improvements to develop people, technos, processes.

Michelin