Data science is a popular topic among employers. The three primary skillsets within the data science umbrella — machine learning, statistics, and analytics — are specialities in their own right. It is rare to find deep skills in all these in one individual.
This makes the fierce competition to bring and keep these skills in-house even more complicated.
Appreciating the differences is the start. Reframing and refining recruitment, upskilling, and retention efforts is the next.
Exploring more outside-the-box options like tapping into machine learning, statistics, and analytics skills 'as a service' from trusted outside parties is becoming a more viable option for many businesses.
what the uninitiated rarely grasp is that the three professions under the data science umbrella are completely different from one another. They may use some of the same methods and equations, but that’s where the similarity ends.