Data scientists are a hot commodity in today’s data-abundant world. Business leaders are relying on data scientists to improve how they acquire data, determine its value, analyze it and build algorithms for the ultimate purpose of improving how they do business. While the job title of “data scientist” was coined by D.J. Patil and Thomas H. Davenport only in 2008, it reached the status of “sexiest job of the 21st century“ by 2012. But what makes for a good data scientist?
In this post, I take a look at several industry experts’ opinions about the skills, abilities and temperament needed to be a good data scientist. Specifically, I reviewed 11 articles that included lists of various data scientist skills (each link directs you to a specific list): Dataiku.com, Smart Data Collective, InformationWeek, Data Science Central, Teradata, Silicon Angle, Gigaom, Forrester, Wired, TDWI, and Dataversity. From each article, I extracted statements (96 in all) that reflected a skill, ability or temperament and grouped them into smaller categories. I let the content of the statements drive the generation of the categories. Some categories had a fairly specific, narrow meaning (e.g., NLP) and others had a broader meaning (e.g., computer science).