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.

#hiring #data-scientist #data #career-paths #career-advice #data-science

There are 5 kinds of data scientists
1.20 GEEK