Monday, June 5

How the diversity of profiles and academic backgrounds enhances IT projects

However, when it comes time to incorporate this type of talent, the task is not easy if you take into account what a good Data Scientist must meet among their requirements.

What does it mean to be a good Data Scientist? What academic background should a person have in order to effectively apply for this type of position? The answers to these questions may come as a great surprise to most.

The reality is that there is not a single training to dedicate yourself to data science, but a variety of related careers, which due to their orientation add a differential value to the professional in their eyes when performing the task.

In the years that I have dedicated myself to building Data teams, I have identified two main factors that I consider must have a good data scientist or at least of value, to be part of my teams. One is the business knowledge in which you want to apply data science, the vision of someone who comes from the commercial area is not the same as the vision of someone who comes from the oil sector; Second, have a academic training related to exact sciences, which offer you a different teaching with the focus on the problem and solve it by collecting hypotheses.

Both factors provide IT projects in general with an important differential that is open thinking, key in a discipline such as data science. In this way, if we put together a work team that has a diversity of backgrounds and profiles, we will obtain a complete and analytical vision of the project that will help its main function, which is to find solutions to different problems.

To conclude, I would like to highlight how important it is to publicize the main aspects and situations that impact the profession in order to avoid confusion and errors in the perception of this type of profile, since although today we find a considerable offer of courses related to the discipline in question, we are in the presence of only a portion of what it means to work in the world of Data Science.

Head of Data and Analytics at NTT DATA