Data Scientist : Understand this cutting-edge and in-demand job around data enhancement.

At school I followed a rather generalist training, my objective was to orient myself towards data-related jobs that deal with all aspects: from data collection to statistical exploitation and machine learning, including storage and management of massive and distributed databases such as big data.

In the continuity of my previous articles, the objective of this last one is to focus on a few key concepts/businesses involved in the data domain and to show how they fit together to reach the current state of the art. My ambition here is simply to define, contextualise and show the intuition and position of these concepts in relation to each other.

In this pitch, I will mainly talk about the Data Scientist profession.

The Data Scientist has several main responsibilities. First and foremost, and as his title indicates, the data scientist is a scientist, he is expected to put his data science to the benefit of the company. His role is to solve the problems of his company through data analysis. He processes, analyses and models the data and then interprets the results.

Data Scientists build new models based on the data, which in most cases differ from the native models of existing systems. Thus, he is most of the time looking for new ways to further exploit Machine Learning and Deep Learning.