Data Scientist: Don’t make these 5 mistakes.

So you landed a job as a data scientist.

You explore really interesting data, come up with a hypothesis, build a model around it, solve the problem and make millions for your company!

This is misleading. This is not the whole picture. This is a mirage.

Let me walk you through some mistakes I made in the first year of my job as a data scientist so that you don’t make those in yours.

1. Not knowing the “kind” of data science my teams needs.

Sometimes, you need to press pause on personal interests and think about what’s best for the product or team rather than just personal progress.

When I started off at work, I was seriously interested in NLP. Almost obsessed with it. I even picked a team that would allow me to work on something like language modelling for the existence of the product. I was ready with my prep on PyTorch, Tensorflow and other deep learning techniques like a Super Saiyan just ready to unleash a transformer model on the tech stack.

Little did I know that at that point in time the product didn’t require work on this part. There were other features that needed improving. The team was focused on other things. My goals weren’t aligned to the big picture. Me trying to…