There are 5 kinds of data scientists

There are 5 kinds of data scientists

In this article, I will be sharing what kind of roles exists in the industry infamously referred to as “data scientists” and debunking the rockstar data scientists requirements.

As companies begin to understand data science product life cycles for their business processes, the expectations of these role and responsibilities are dynamically changing.

Often I hear, I am a data scientist too. But, how is that my job entirely different from the other person who holds the same title?

Let’s debunk the roles and name them out!

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Photo by Rohit Farmer on Unsplash

One of the things I love absolutely about this profession is that one can’t just simply be a_ statistician, a quick programmer, or an experiment modeller._ The role requires multiple technical and soft skills while being bias to the action. That is easier said than done - yet, this is exactly what companies are seemingly exploiting, more so unwittingly.

Here is what one could be:

The jack of all trades and master of one!

What companies who have no data science roadmaps want:

The jack of all trades and master of ALL!

There are FIVE kinds of data scientist roles I have categorised based on my past experiences, interviews & offers.

  1. Hacker Data Scientist
  2. Analyst Data Scientist
  3. Research Scientist
  4. Machine Learning Engineer
  5. Customer Data Scientist

And, for the mercy of sciences, there is** NO WAY** a single person is fit for all kinds of roles.

Let’s begin diving into each one of them.

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