Profiling the Different Types of Data Scientists: Which One is Right for You?
Published in Winter Conference on Business Intelligence, 2016, 2016
Recommended citation: Sanaz Bahargam, Theodoros Lappas WCBI 2016.
Abstract
The growing popularity of data-driven decision making, coupled with the increased availability of affordable infrastructure for storing large volumes of information, have established data as a firm’s most valuable asset. To take advantage and monetize from this asset, a firm needs talented employees with the skills required to analyze large data repositories, identify opportunities to improve the various aspects of a firm’s operations, and inform strategies that can be used to fully take advantage of such opportunities. While such individuals have always existed and held various titles within firms, the era of Big Data and Analytics has brought them together to create a new cast of “data scientists”. Famously dubbed as “the sexiest job of the 21st century” , this new role has become a hiring priority for firms across industries. In 1 addition, the ever-increasing demand and highly competitive salaries have established data science positions as highly desirable targets for fresh graduates and experienced workers who feel that they have the skills required to transition to data scientist roles. For all interested parties, the key question is the same: what is it that makes a good data scientist?