16 May
2019

Top 3 Skills of a Data Scientist

Discover the main skills of a data scientist!

Human Resources
Industry 4.0
Smart Factory
Les 3 principales compétences d'un Data Scientist

data analyticsNowadays, several technologies allow companies to obtain a large amount of data. The return on investment of these technologies depends largely on the actions that are taken from the data collected. Businesses are changing and increasingly feel the need to base their decisions on solid, reliable data. You will not be surprised to learn that the role of a data scientist is a role increasingly in demand within organizations.

What is a data scientist?


The role of data scientist is to manage, analyze and interpret the data, while taking into account the organizational reality, which requires a very developed business sense.

3 fundamental areas of expertise of a data scientist:

Technical competencies:

The data scientist must have programming knowledge with languages such as R or Python as well as knowledge of computer architecture and databases. He or she must be able to adapt to different IT environments and have intellectual agility to learn and constantly adopt new methods. This person must master data manipulation and be comfortable with several different data structures.

Analytical competencies:

The role of data scientists requires to be an expert in solving complex problems. In this category are skills in advanced statistics, machine learning, advanced mathematics, modeling, simulations, artificial intelligence, etc. In general, the fields of study in science, technology, engineering, mathematics and physics make it possible to develop the analytical skills sought and make it possible to practice solving scientific problems.

Business competencies:

The data scientist must understand the corporate environment in which the data evolves. In the field of data science, successful projects are those that are based on a specific situation and that end with concrete solutions that can be integrated into the work environment.

 

 

Data scientists are in demand more than ever. It must be remembered, however, that their success requires first and foremost reliable and sufficient data. Real-time production tracking solutions or data analytics are definitely avenues to consider!

 

Want to learn more?
Download the ebook
Related blog articles

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
28
Juin 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

English
10
Juin 2019

Serez-vous capable de rattraper les leaders de l'industrie - Partie 2

French
20
Nov 2019

Comment améliorer la production en boulangerie avec les solutions d'industrie 4.0

French

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
27
Nov 2023

Vos ventes sont en baisse, mais la rentabilité ne doit pas nécessairement l'être

Découvrez comment des technologies telles que le monitoring de la production aident les entreprises manufacturières à maintenir leur rentabilité alors que les ventes diminuent.

French
24
Nov 2023

Votre guide de la transformation numérique avec Worximity

Avec Worximity, vous n'obtenez pas seulement un fournisseur de technologie, vous obtenez un partenaire qui vous accompagne tout au long de votre transformation numérique manufacturière.

French
23
Nov 2023

Pénuries de main-d'œuvre dans le secteur manufacturier - Comment le monitoring de la production peut aider

Alors que les pénuries de main-d’œuvre continuent d’entraîner des pertes substantielles dans le secteur manufacturier, il est temps de considérer le monitoring de la production comme l’un des outils permettant d’atténuer certaines pertes.

French