What are the career opportunities as a Data Scientist?
With the digital transition and the Big Data, many of the professions of the next decades do not yet exist. Professions are changing and evolving, specializing in digital. But there are already career opportunities in data processing, which is becoming indispensable for all companies, regardless of their size. One Data Scientist has skills and qualities that are already very actively sought after by recruiters.
Data Science, what is it?
Scientific methods and Data Science tools are used to exploit data. This involves using processes, algorithms and devices to extract information relevant to companies and their field of activity.
The data can come from all kinds of devices and media: it can be smartphones, the Internet, but also sensors of connected objects, CRM information, etc. The objective is to enable decision makers to make the best possible choices for their sales or marketing strategy. Thanks to the Data Scientist, they are able to rely on the most relevant information in order to achieve their goals.
Why is it now necessary to process the data?
All sectors of activity, without exception, are concerned by digitalisation. With the development of the IoT, data is coming from all kinds of everyday objects. For retail companies, customer information is indispensable for creating personas, adapting customer paths, implementing content and marketing strategies.
For companies in the industrial sector, the data can also be used to prevent possible breakdowns, improve maintenance and monitor equipment. The better it is processed, the easier it is to improve logistics and reduce costs. There are two main families of data:
- Connection data: all the information relating to the network, the operator used, the duration of the sessions or the amount of information exchanged.
- Raw data: the immediate information collected and provided by the connected objects before analysis. In its raw state, it is not readable, so it must be analyzed to generate value. This value differs according to the company’s field of activity and its core business.
But in the age of Big Data, there are increasing volumes of data to be processed. It is difficult for humans alone to use this information to draw logical conclusions. That’s why a Data Scientist is trained in the methods, tools and systems to understand this information and draw viable models for the business.
What kind of career can a Data Scientist have?
The Data Scientist’s profile is coveted. Young graduates or young workers with some initial experience know that they will have no difficulty in finding a position quickly. Turnover is relatively flexible and usually revolves around three years.
During this period, the professional has time to explore all the themes of his company, before his curiosity pushes him in another direction. You have to be curious to practice this profession, which is one of the qualities sought after by recruiters. Professionals must be able to adapt to all kinds of business issues. They can, for example, move from agri-food issues to issues specific to ready-to-wear clothing by changing jobs.
However, this ability to adapt must not overshadow the passion for the job. Many professionals are driven by a real vocation. For many, certain fields such as digital marketing are less attractive than disciplines such as aeronautics or medicine.
In fact, the Data Scientist has the opportunity to be recognized for the value it adds to the products or services to which it contributes. He can work in relation with other experts, or even real communities of researchers. There is therefore almost an academic dimension to the exercise of this profession, which implies constant training and constant monitoring.
What is the training for this job?
To be a Data Scientist, you must have a Bac +4 or Bac +5 in marketing, statistics, management or IT. Training courses for this profession are currently being created in many establishments, as the profession is still young.
EDC Paris Business School offers a M.Sc In Data Science & Business Analysis, which is perfectly adapted to this perspective. This program combines both a business and a technical approach. It trains students to process data to assist in strategic decision-making in many different fields.
Data visualization, structuring, analysis and problem solving are at the heart of the teachings. It is a sandwich course, deepening the four pillars of Data Scientists which are information systems, mathematics, areas of expertise and communication.
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