3 years ago

Category: Software

In my opinion, the most important groups you can segment data scientists into are those who write code used in production, and those who do reporting.

This does not mean they are not data scientists, people in these roles benefit from knowing machine learning, the ins and outs of data, and general programming skills.

So, the primary issue I take with data science education is that there seems to be and not a lot of focus on engineering skills.

I’ve argued previously in Towards Data Science about the gap in programming ability and the struggle even many in technology have with basic programming here, but these are some of my recommendations to learn: Once you have done all of that I would move onto learning about DevOps, since it makes you more efficient, easier to collaborate with, and the best engineering teams place a lot of emphasis on DevOps practices.

I think once you get to the point that you have comfort in doing data science on the cloud, if you don’t look more attractive as a candidate for a data scientist job, you will at least have a better understanding of how the work of a data science engineer gets put into place.