The data scientist is one of the most recent professional roles to emerge in the IT world. Their main task is to analyse data on behalf of a company in order to provide forecasts, behavioural schemata and algorithms for use in building profits.
Obtaining the data is straightforward, and this can be achieved by any analyst with minimal skills, but detailed analysis (especially non-structured) is highly complex and requires considerable experience. For these reasons, this new profession is among the most sought-after and highly paid in the entire IT sector.
Big Data: why it’s relevant
Data scientists work mainly with what is defined as Big Data. This collection of data is gathered from a variety of sources and is of great value to companies. The type of data gathered is divided into two categories: structured and non-structured.
Structured data is that which can be easily purchased and organised into categories automatically, using purpose-built programs. This includes website traffic, sales figures for a specific product, GPS co-ordinates harvested from smartphones and so on. In general, this kind of data is easier to analyse and interpret.
Non-structured data on the other hand, is the data scientist’s bread and butter and requires much more experience and ability when it comes to its interpretation. This category includes reviews posted by users, messages on social networks, feedback, emails, videos and all other input deriving from real people.
It is these people who are of the utmost value to companies, since they allow them to evaluate customer behaviour, reactions to new commercial offers and monitor the commonest behaviours. The interpretation of this data allows companies to develop more targeted strategies.
The ideal training path for a data scientist
There are many ways to become a data scientist, even though the most common one is to study for a degree. This could be in a variety of subjects, but the most suitable ones are in the economics field.
It is important to bear in mind that this professional figure must also possess transversal skills. That is to say that, depending on the sector of the company he is analysing data for, specific skills will be required (working in marketing is different from analysing data in the healthcare field for example).
There are some specialised courses which allow aspiring data scientists to fine-tune their skills and fill any gaps, by offering them more targeted training. Another good way to enhance their CV is to achieve specific certifications from authoritative organisations in the field of data analysis.
Among the basic skills that every good data scientist should possess are programming, quantitative analysis, an understanding of the product, communication skills and team-working.
The best employment opportunities for data scientists and earnings
All sectors, especially those doing business online or in direct contact with the public, have a considerable quantity of data to be analysed. The data scientist can easily find work in many different sectors, but the markets offering the most opportunities include:
- social networking;
With the right skills and good training (whether previous or specialised), the data scientist has many career options to choose from. It should not be ignored that the average salary for those in this profession ranges from approximately 100 thousand to 168 thousand dollars per year.
Translated by Joanne Beckwith