MIT Sloan Management Review Article on How Large Companies Can Grow Their Data and Analytics Talent

Companies need to identify the type of talent they need in order to become data-driven.

While many companies are hiring data scientists and other types of analytical and artificial intelligence talent, there is little consensus within and across companies about the qualifications for such roles. The term data scientist might mean a job with a heavy emphasis on statistics, open-source coding, or working with executives to solve business problems with data and analysis. The idea of data scientist “unicorns” who possess all these skills at high levels was never very realistic.

As the job has grown more popular and sought-after, an increasing number of professionals have begun to use it to describe their role. Colleges and universities have responded to the demand as well by offering hundreds of new programs on data science and analytics. But the skills taught in such programs vary widely, and some universities offer multiple programs with different emphases. For both newly hired and experienced employees, titles such as data scientist and quantitative analyst are not likely to be good guides to their actual capabilities.

About the Author

Thomas H. Davenport (@tdav) is the President’s Distinguished Professor of Information Technology and Management at Babson College, as well as a fellow at the MIT Initiative on the Digital Economy and senior adviser to Deloitte’s Analytics and AI practice.

Learn more about MIT SMR.