As more and more large organizations now start to implement data science as a strategic capability, this is a growing problem. There seem to be three solutions. Companies may find a PhD who has it all: excellent analytical skills and excellent people and domain skills. Or they may hire a PhD with excellent analytical skills and retrain them with respect to people and domain skills. Or you can split the data science function in two: Data Engineering and Analytics Translators. The first two solutions are not our favorites.
Find the needle in the haystack
Of course, they do exist, data scientists with excellent analytical skills and excellent people and domain skills. And we congratulate you, if you have one. Cherish her! Others will try to hire her away from you. And if you do not have one, you may find one. But they are scarse – and very expensive. And there is always the risk of ‘prima donna’ behavior. Or they may decide to launch their own startup.
Retrain your excellent analytical PhD
Yes, in theory you could. But depending of the degree of people and domain skills of your PhD it may take a long time and a lot of effort. In general, for most people it is easier to learn new cognitive skills than it is to change behavioral patterns. Especially, if those behaviors have led to the success that people praise you for or when those behaviors are deeply engraved in your brain.
Besides, many data scientists don’t feel very comfortable with or even outright hate ‘internal politics’. Yet, that is an important skill to make data science solutions successful.
So, both solutions have significant drawbacks. To be honest, we may simply be asking too much if we want the whole package of excellent analytics skills, excellent people skills and excellent domain skills in one person. And it makes a company vulnerable and reliant. There is a better solution.