While data scientists have many resources in their tool belt, our research shows that proficiency with data mining and visualization tools consistently ranks as one of the most important skills in determining project success.
We used two methods to rank data science skills. The first way was based on the frequency with which professionals possessed the skills. This method identified data science skills that are common across data scientists. The second way based on the correlation between the data scientists’ proficiency in the skill and project outcome. This method identified data science skills that are linked to project success. Comparing the results using these two ranking methods lead to some interesting conclusions about specific data science skills. Over the next few weeks, I will be exploring specific data science skills and what these findings mean to data scientists and businesses that hire them.