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
Top 3 Skills of a 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

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
17
Jul 2018

Video: The Journey to Smart Manufacturing

English
27
Jul 2018

How Real-time Data Will Impact Your Food Manufacturing Operations

English
13
Jul 2018

5 Examples of How IIoT is Changing Manufacturing

English

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
28
Jun 2023

Investir dans l'industrie 4.0 : c'est désormais plus important que jamais pour les manufacturiers d’agroalimentaire et boissons de toutes tailles

La clé est d'adopter l'innovation pour naviguer dans des conditions en constante évolution et rester à l'écoute des demandes des consommateurs, tout en maximisant la rentabilité.

French
28
Jun 2023

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

Faced with challenges that include labor and raw material shortages, tightened regulations ,and skyrocketing costs, companies like you are struggling to produce and price products to meet the demands of increasingly cost-conscious consumers and anxious stakeholders alike.

English
27
Jun 2023

Au-delà des chiffres : maximiser le retour sur investissement dans le secteur manufacturier grâce à l'analyse de données

L'intelligence des données provient de chiffres bruts. Ces informations doivent être analysées et traduites en actions ayant un impact sur l'entreprise. Mais avec des données qui s'accumulent plus vite qu'elles ne peuvent être transformées en analyses de données manufacturières, les entreprises ratent des opportunités.

French