You make some interesting points, and thanks for taking time. I’d agree with the power of these ‘consultancy skills’, they definitely add more value to a data scientist’s repertoire. The way I had organised the key skills, I had included some of these aspects under the central bucket of Data-bootstrap skills and it includes items from your list like : a) passion for data/job, b) content skills or ability to intake and layout the approach to a problem, c) presentation and basic story telling skills.

However, the soft skills you’ve mentioned (people-learning-time management) are not called out in any of the skills I’ve laid out, and I think thats a useful point to add. Perhaps, they could also go into the bucket of bootstrap skills, since all of these are critical for all the roles in Data science.

The point I’ve made on Domain skills is a tad different. While there are a many roles in data science who switch from domain to domain and across business problems, there is also space for specialists who wish to work in just one domain and get into deep-vertical analytics ex. Financial risk modeling.

I’ve seen the need for such people in projects, in addition to the data consultants or data analysts who might move in-and-out of the domain on a short-term basis; these can be complementary roles on the same project. Additionally, this fits in well for people who have 10 to 15 years deep domain expertise in an industry and want to pick up data science skills and combine both to make a new career. I’ve seen such individuals successfully transition and get hired into such new roles in the industry.

Hope this clarifies. Happy to chat further if you have seen other perspectives in your experience.