Dissecting the flavors of data science

Now that we have defined some of the critical aspects of the role of a data scientist, it is clear that the role often covers many different skills. Data scientists are frequently asked to perform a variety of data-related tasks, including designing database tables to collect data, programming ML algorithms, understanding statistics, and creating stunning visuals to help explain interesting findings to others, but it is difficult for any single person to master all of these skill areas.

Therefore, we often see data scientists who are particularly skilled in one or two areas and have basic competencies in the others. Their talents could be considered T-shaped, where they are proficient across many areas such as the horizontal line of a T, while they have deep knowledge and expertise in a few areas such as the vertical portion of the letter:

Figure 1.2: Example of the ‘T of Competencies’

While this...