In today's world and society, companies have become increasingly data-driven and, as a result, more focused on getting value from data. Thus, the whole field - data science - has grown rapidly and become more popular. Thus, it is easy to conclude that the demand for specialists in this field should also increase.
If we have previously written more about the different roles in the data science team (about these specialists), this time we will write about how to get to their positions. As there is no single standard way to enter the field of data science and there are several possibilities, we will study this topic in more detail and review the main university undergraduate specialties that could best prepare for a career in the field of data science.
But before that, let's write down the main skills needed to deal with data science. Although it can be categorized in many ways, we are currently doing the following:
- math and statistics skills
- programming skills and computer skills
- business skills-knowledge and problem solving
In the following, we will look at how the relevant skills are covered in the selected undergraduate specialties.
1. Mathematics
A degree in mathematics is probably one of the most versatile degrees from which the acquired knowledge can be used in a wide range of fields. After completing this specialty, in addition to strong knowledge of mathematics, there is also (depending on the choice of subjects) basic knowledge of programming as well as statistics. Of course, learning mathematics develops general analytical skills and critical thinking.
A strong foundation in mathematics and statistics is very important in data science, but those who have obtained a degree in mathematics could also think about some extra learning of IT or statistics if they want to start in the field of data science.
2. Statistics / mathematical statistics
Studying statistics or mathematical statistics is probably one of the most universal options, as curricula are generally designed to cover mathematics, statistics and programming. So it is a very preparatory degree to deal with one role or another in data science. Understanding the business side and making connections is definitely facilitated by making personal projects and participating in professional internships.
3. Informatics, computer science (IT)
Informatics or any other specialty of information technology creates very good preconditions for working in the field of data science. Similar to the above specialty, problem solving and analytical thinking are also important here, but the most important advantage is, of course, programming skills, which are very important in data science. The need for technical knowledge also varies depending on the later course of action (eg the work of a data engineer is probably more technical than that of a data analyst).
As the study of mathematics also plays an important role in this specialty, it could certainly be considered (depending on the position) to improve the knowledge of statistics. Of course, business knowledge is created in the course of work, but it can also be developed in advance (eg by doing personal projects or participating in hackatons ).
4. Economics
Studying at the Faculty of Economics has a great advantage in terms of business knowledge and connection to the real world. As it is more business and entrepreneurial, linking it to data-drivenness creates a strong whole. Obviously, such a combination is particularly suitable if you are planning to move into the financial sector or related sectors.
Compared to the previous examples, there may be less in-depth study of mathematics in economics or any other similar field, as well as subjects in statistics and programming. Therefore, as an economics student, it is definitely beneficial to strengthen these very skills to the next level in order to gain a broader basic knowledge when entering the business world.
5. Physics
Like mathematics, a degree in physics is a very diverse field and these skills can be applied in many different fields. In order to continue working in the field of data science after studying physics, it is very reasonable to learn more about IT and statistics.
All in all, we managed to cover several university disciplines that would be the most suitable for a career in the field of data science. Therefore, if you are interested in taking a closer look at data and data science, then in addition to your personal strengths and preferences, you should consider the above overview when choosing a university undergraduate degree, as this could make your choice easier!