Bob Hayes presents a study that hybrid roles optimize analytical efforts

The hybrid data scientist is one whose work reflects many different data science roles. Hybrid data scientists, compared to data scientists who play a single, narrower role, possess deeper knowledge in particular data science skills such as machine learning, managing unstructured data and optimization. Organizations can leverage their deeper knowledge to improve their data science efforts.

The success of a data science program rests on the skills of the data scientists doing the work. Because different types of data scientists have unique skills, it’s important that you get data scientists who possess the skills you need to address the problems you want to solve. While our earlier reporting focused on understanding the difference among four types of data scientists (Business Manager, Developer, Creative and Researcher), we want to now understand the data professional who self-identifies as multiple types of data scientists, the hybrid data scientist. Do these hybrid data scientists possess more skills than their counterparts?