Data science as a branch of science has become more and more popular over the years, and in connection with the information age, data as an object has a very important role in business processes.
As a result, many entrepreneurs have already turned their attention to the application of data science in their own companies and have thus hired specialists to turn huge amounts of data into valuable information. But who exactly would be needed, and which are those profiles that should be part of a data science team?
In the following, we review the key roles that should definitely be covered in one successful data team.
1. Data Analyst
The main role of data analysts, as the name suggests, is to analyze various data, and to a very large extent. Data analysis can take place on the scale of large projects (eg the development of different financial models in financial institutions), but they can also be limited to solving individual tasks for a specific purpose ( ad hoc tasks). Knowledge of statistics and maths is also very important in this role in order to understand the nature of the data and to apply various statistical tests to draw conclusions. In addition, data analysts also work on the data visualization and business intelligence (BI) side, which involves creating visual reports and creating key performance indicators (KPIs) that help assess a company's performance.
2. Data Scientist
The main task of data scientists is to find valuable information from existing data and to identify patterns / trends that help to develop business. In addition to data analysis, they use different (machine learning) models and algorithms to make more accurate decisions, so it is very important to know which model / algorithm to apply in which situation. In the role of a data scientist, the communication side is also very important in order to successfully and clearly explain the results found to other team members or the business department.
3. Data Engineer
The role of data engineers is somewhat different from the previous two, because they are not so much about finding value in data, but above all about the architectural side - they build, test and manage data warehouses and databases, create tables where they can get data and much more. They make sure that the data update works and that the data can be used comfortably, so they create a basis for further use of the data. Thus, their core activities in the data science team are related to the architectural side.
4. Business Analyst
In many cases, business analysts are also involved in the data analysis team, and then their main role is to act as a link between the business side and the analytics department. Regarding their daily duties, it is mostly similar to data analysts - data analysis and drawing conclusions. The main difference is that business analysts have a greater focus on the business perspective and, depending on the company, also have a greater role in making strategic decisions.
As the overview shows, the structure of the data science team is very diverse and consists of different profiles. Therefore, when assembling a team, it is important to keep in mind the circumstances in order to cover business requirements and have sufficient data competence. Thus, it turns out that at least these 4 positions should definitely be filled in a comprehensive and development-oriented data science team.