Data Scientists should act more like Product Managers

There is a lot of evolution in the realm of data-science, with some of the evolution such ass AutoML chipping away at some of the core tasks of a data-scientists, freeing valuable time. This has led some to see the evolution of data-science towards a product manager role or more towards engineering:

Every time we ask our guests about the direction data science is heading in, we get one of two answers: either 1) data science is becoming a product/business role, and data scientists need to think like data-savvy product managers; or 2) data science is becoming an engineering problem, and data scientists need to think more like engineers.- TDS blog post

I had already touched on that on some of that evolution in previous article. But never fully detailed why or how data-scientists should be tackling this shift. People often talk about DataScientist being of Type A or B, and to a certain extent that separation is as much a reflection on the data-scientists skills than a reflection on the organization hiring them and how to be best effective in that organizational context.

One of the common myth about data-science is that it is

”80% data wrangling / 20% doing analysis/ML”

Data-science is not just a set of data manipulation and Machine Learning algorithm or…