You can be a good data scientist by sitting at your computer. After all, the job description involves poring through huge quantities of often disparate data to find insights that may prove helpful in every aspect of a business, including marketing, logistics, and human resources.
It also includes cleaning data, dealing with gaps, and sifting through incomplete poor definitions. But great data scientists know they must do more. They recognize that there are nuances and quality issues in the data that they can’t understand while sitting at their desks.
Author: Thomas C. Redman