Data scientist: what he does and why he is important for companies

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Defined by the Harvard Business Review as the most fascinating profession of the 21st century, that of Data Scientist is a position increasingly in demand by companies in Italy and abroad.

A demand destined to increase even more in the course of 2022, according to the World Economic Forum, which includes the Data Scientist among the 21 most 'fashionable' roles in the digital economy.

But what exactly does a Data Scientist and what skills are needed to pursue this career?

Data Scientist: who he is and what he does

The Data Scientist is a highly specialised professional, capable of managing raw and processed data in order to extract useful business value from it, through data-driven strategies and models.

The sector in which he or she operates is that of data science, i.e. the discipline, belonging to the branch of Artificial Intelligence, which studies methods and techniques aimed at extracting meanings and useful information from data.

The Data Scientist often works in synergy with two other figures: the Data Engineer and the Data Analyst.

The first deals with Data Pipeline, the infrastructure that transports the data to the front-end tools and has the task of providing the Data Scientist with the data in a format suitable for the analysis phase.

The Data Analyst, on the other hand, represents the link with the business lines and manages descriptive activities.

The Data Scientist, instead, specifically deals with:

  • Organising data in analysis-compatible formats

  • Analysing and processing data in order to extract useful and valuable information for the business

  • Data Visualisation

  • Descriptive and predictive reporting

  • Proposing and promoting data-driven strategies

The data it deals with can be of three types:

  • Human generated: generated by users through websites, social networks, etc.

  • Machine generated: from autonomous sources such as GPS, monitoring systems, etc.

  • Business generated: a set of data belonging to the two previous categories, used within the company.

Machine Learning, AI, knowledge of programming languages (e.g. SQL, Python and R) and mastery of data-base management enable the Data Scientist to do his or her job better and generate value for the business.

How to become a Data Scientist: study paths and skills

It is now well understood by companies how crucial it is to define plans and make decisions, exploiting the vast amount of information that the company produces and receives every day. In this scenario, the professional figure of the Data Scientist acquires strategic importance.

Pursuing a career in data science, therefore, appears to be an interesting opportunity for young people with an interest in STEM.

To become a Data Scientist, you first need a university degree in Mathematics, Engineering, Physics, Computer Science, Statistics or Economics. To this must be added skills in programming languages, Analytics and Machine Learning.

Master's degrees in Data Science and training courses dedicated to the various sectors in which the Data Scientist can work, ranging from finance to PA, complete the training.

In fact, the list of sectors that may need this professional figure is almost endless. This is because the development of data-driven strategies, built on trends, customer/user needs, market movements, today, is indispensable to gain and maintain competitiveness in relevance.

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