20/05/2021
Some folks asked me how they can build career in Data Science. Here are few points I listed last night as a starting poing
How do Engineers transition into Data Science?
There are mainly two tracks for data scientists, one is product analytics, and the other is machine learning; the latter requires more engineering skills.
Unless you are really into product and business, becoming a ML scientist/engineer is better for you to leverage your strength.
Start with foundational machine learning course, and then learn how to implement machine learning models in production.
When learning, focus on the fundamentals, and make sure you can explain the basic concepts. You don't have to be an expert in both computer vision and NLP; pick one area to go deeper.
If you have a good foundation, you can always build other skills on top of that. And most hiring managers believe this.
However, courses won't be enough. Try to find ML projects on your team, and build an end-to-end ML solution - this will make you stand out compared to other candidates.
So, focus on the fundamentals, gain hands-on experience, and put your ML projects in production.
Don't forget to interview during the process to get feedback, and don't wait till you feel 100% ready - because you'll never will.
You'll be good enough at some point for a role. By Gaurav
