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.
18
Avril 2019

Industrie Agro-alimentaire: Les vraies opportunités résident dans l'intelligence artificielle

French
15
mai 2019

Un nouveau regard sur l'industrie de la production alimentaire avec l'intelligence artificielle

French
26
Avril 2019

Les robots et l'intelligence artificielle font leur entrée dans l'industrie alimentaire

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.
20
Fév 2018

Worximity fera partie de la super grappe Scale AI

Worximity est fière d'annoncer sa participation à la super grappe Scale AI des chaînes d'approvisionnement intellligentes.

French
1
Oct 2019

Big Data and Budgeting

In this article we’re going to dip our toes into the near future of manufacturing business and discuss Big Data and Budgeting.

English
20
Fév 2018

Worximity will be part of the Supercluster Scale AI

Worximity will be part of the Supercluster Scale AI (Supply Chains And Logistics Excellence.AI). It's mission is to shape a new global supply chain platform and bolster Canada’s leadership in artificial intelligence (AI)

English