The Type A vs. Type B Data Scientist
The data science unicorn is an intriguing notion which does not fall far short of its name. It is the idea that there are some professionals who have mastered a broad range of skills in data science, from pure data analysis to software engineering. With data science demanding such a wide spectrum of competencies, it is no surprise that such elusive practitioners are referred to as data science unicorns.
Two types of data scientist are emerging: The Type A and Type B Data Scientist.
The Type A Data Scientist: This type of data scientist normally hails from a very strong statistical background and as such, takes a keen interest in using data science for pure analysis. Their skills complement a core statistics curriculum, namely data wrangling, data cleaning, data visualisation and good data write-ups. They are adept at extracting information from data to interrogate and answer complex questions.
The Type B Data Scientist:
While these data scientists will have some statistical knowledge, they are typically much stronger programmers and may be experienced in software engineering, software development and the likes. They build and implement data products and seek to find practical ways to make their findings impact day-to-day business operations.
The boundary between the two types of data scientist is blurry but having knowledge of both domains is advantageous. As data science evolves, it will be increasingly important to keep the two types of data scientist in perspective and find the right combination of skills that works best for your particular business.
For more on this topic click here for a great writeup by Conor Dewey.