What it needs to be a "successful" data scientist?

Defining success for a Data Scientist isn’t hard since there is only 1 parameter to satisfy i.e.
Satisfaction of all the involved stakeholders.

This again can be achieved by either solving the problem faced by them/finding an underlying problem then solve it or help the stakeholders do their jobs by optimising some to fetch better results.
This will can be or not be a team effort depending on the type of business the Data scientist is catering to.

  • For a Product based business where the requirement
    is strictly internal the team size is usually small with
    long project tim lines but requirement of rather
    specialised skill set for that domain
    E.g. Walmart 2nd largest company in the world going
    by the market cap by domain is in Retail would much
    rather hire someone to have experience in retail
    domain only

*For a Service based business where the core business
is to help other businesses by sourcing Data science
work will have requirement for someone who is Jack of
all trades

So, the skill set requirement is divided into 2 parts one being core skills like ML/DL/Stats/BI and other being Business acumen. Where the latter is always discounted for due to steeper learning curve that former.
This discounting usually comes to bite back when the stakeholders are not technically sound but are business folks that need translation of data into pure business terms for consumption.

Thus for that conclusion ML /DL skill set in undeniably important in both types of organization with ability to translate data into business jargon a key skill that is highlighted to be the difference between a “successful” data scientist and a run of the mill data scientist.