{"id":54924,"date":"2026-08-24T11:52:34","date_gmt":"2026-08-24T09:52:34","guid":{"rendered":"http:\/\/www.turner.nl\/uncategorized\/six-archetypes-of-data-scientists-choose-your-color\/"},"modified":"2026-08-24T11:52:41","modified_gmt":"2026-08-24T09:52:41","slug":"six-archetypes-of-data-scientists-choose-your-color","status":"publish","type":"post","link":"https:\/\/www.turner.nl\/en\/artificial-intelligence-2\/six-archetypes-of-data-scientists-choose-your-color\/","title":{"rendered":"Six Archetypes of Data Scientists\u2014CHOOSE Your Color"},"content":{"rendered":"\t\t
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Artificial Intelligence<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Six Archetypes of Data Scientists\u2014CHOOSE Your Color<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Data scientist Egbert Clevers has to explain \"what he actually does\" all over again at every family gathering. To make his life\u2014and that of organizations looking to hire data scientists\u2014easier, he presents six archetypes of data scientists. CHOOSE your color! <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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Six Archetypes of Data Scientists\u2014CHOOSE Your Color<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The annual family day: the perfect opportunity to catch up on work and personal life. One is a journalist, the other works in Healthcare\u2014professions that can be explained in a single word. But as a data scientist, I always have a hard time explaining exactly what my job entails. <\/p>

The same is true in the workplace, by the way: plenty of skeptical looks or plenty of (often incorrect) assumptions. I think these assumptions stem from the examples of data innovations that everyone sees around them. With technical feats from Google or YouTube, data science seems like a goldmine of smart apps and deep learning<\/em> algorithms .<\/em> With KPI dashboards in the business world, data<\/em>science seems like a way to (finally) make unstructured data understandable. With in-depth analysis of scientific data, data science seems to be mostly about statistics. In short: there\u2019s quite a wide range of understanding regarding the meaning of data science. Yet in the Netherlands, many thousands of organizations employ one or more data scientists or are on the verge of recruiting them. I sometimes wonder how many of those organizations actually know who or what they\u2019re really bringing on board. Time for some clarification! <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Data science as an umbrella term for a range of skills<\/p>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Just for fun, I took a look at the LinkedIn profiles of about a thousand professionals who describe themselves as data scientists, as well as a few other data-related roles for comparison. There appears to be significant clustering in the competency profiles of data scientists. This is evident from a latent class analysis, as shown in the figure below using two principal components. <\/p>

That brings me to six archetypes:<\/p>

  1. The data scientist with a strong background in mathematics. Understands the statistical basis of analyses and thus has a solid \u201ctoolbox\u201d of data analysis methods. Often has a background in physics or mathematics. <\/li>
  2. A data scientist with a background in development. Programs and builds (web) applications with a data component. Often draws on a background in life sciences<\/em> or sustainability<\/em>. <\/li>
  3. The specialist in artificial intelligence (AI). Capable of handling technically complex problems, such as the automated processing of images or text, often using deep learning<\/em>. <\/li>
  4. The business consultant. Combines a background in economics or business administration with a knack for data to tackle everyday challenges in the business world. <\/li>
  5. The (technical) data consultant. Has experience with various software packages across different markets. Well-rounded skill set. <\/li>
  6. The data science “manager.” Translates data expertise into strategy and policy. Possesses both technical data skills (particularly in commercial software packages) and management skills. <\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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