A data scientist must know how to approach the extent of any problem; it means identifying features and figuring out the question that how to frame the desired answer is the key to become the most wanted data scientist.
Basically, it is important for a data scientist to clearly make or break the data methods and apply them to solve any problem at the end. There is only one step difference between success and failure to be a perfect data scientist, because a small mistake can make or break his work completely so knowing the basic skills is necessary for them; like SQL, Microsoft Excel, Python, statistical programming, data visualization, and finally the critical and presentation skills to go hand in hand.
For a data scientist, being able to tell a compelling story of data and getting your point across to keep the audience engaged is very important. But the presentation does not always come naturally to everyone and it is completely fine! With some helpful tricks, you will get to know how to do a comfortable presentation of your critical skills.
However, including the above things, it's also important for a data scientist to know machine learning and predictive modelling that are quickly becoming the hottest topic in the field of data science.