Amid all the talk of big data, no doubt you come across the newfangled job title “data scientist.” Various definitions, purposes and forecasts of this line of work blanket headlines daily. I found this in-depth interview with Data Scientist Consultant John Hooks helpful to identify what the role actually entails: big data predictive analytics.
In other news, Information Management’s Big Data Talent War: 10 Analytics Job Trends, trend No. 7 revealed that Scott Sorensen, Ancestry.com’s Senior VP of Engineering, is beefing up his team with data scientists. Sorensen offers his definition of a data scientist as someone “skilled in taking a statistical approach to algorithm development. Many times they’re statisticians, and they understand how to create statistical models that allow you to use massive amounts of data to develop algorithms.”
Of course with anything new, there are obstacles. “One of the challenges our industry faces is we presume access to large amounts of data also comes with a button that says ‘Insights …’” said Alexandra Drane in this AllAnalytics.com slideshow featuring nine data scientists. Will the data scientist ensure insights are found through appropriate technologies and (sometimes controversial) organizational change?
I asked six industry experts, including:
- April Wilson, Digital Analytics 101
- Bill Franks, Teradata
- Dean Abbott, Abbott Analytics Inc.
- James Taylor, Decision Management Solutions
- John Elder, Elder Research
- Richard Boire, Boire Filler Group
if they thought organizations were moving toward emerging roles like the data scientist and here’s what they said.
What is your perspective on the data scientist?