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!
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!
The jack of all trades and master of ALL!
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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