A lot of people in this thread are focusing on technical tools, which is normal for a discussion of this type, but I think that focus is misplaced. Most technical tools are easily learnable and are not the limiting factor is creating good data science products.

https://towardsdatascience.com/data-is-a-stakeholder-31bfdb6...

(Disclaimer: I wrote the post at the above link).

If you have a sound design you can still create a huge amount of value even with a very simple technical toolset. By the same token, you can have the biggest, baddest toolset in the world and still end up with a failed implementation if you have bad design.

There are resources out there for learning good design. This is a great introduction and points to many other good materials:

https://www.amazon.com/Design-Essays-Computer-Scientist/dp/0...