Data science requires interdisciplinary skills.
As a data scientist you should have a very good knowledge of statistics in particular of inferential statistics. You have to eat algorithms for breakfast, data mining for lunch and machine learning for dinner. That means that you know at least one programming language as R or Python not to mention SQL queries and NoSQL queries of key-value pair databases such as MongoDB.
An OOP language such as Java can help you even more, especially when you want to use distributed computing and cloud.
At the end knowing quite well the data domain may be essential in order to deliver a non mediocre work. But knowing the data domain requires a cross-functional knowledge and interdisciplinary skills and so on recursively.
It is in this combination of skills and trasversal knowledge that stands the magic of data science.
So for me there is only one type of good data scientist. That is the one which better integrates in his mind and hands all the knowledge and skills I mentioned above. Depending on the combination of those skills you have a good data scientist. Or just a programmer. Or just a statistician.