With the boom in big data and advancement in technologies built to collect and manage the petabytes of information, there is still a bit of a gap left in the analysis and application of big data.
In many companies, the marketing, sales and/or designated business analyst professionals are responsible for synthesizing and drawing conclusions, but often times, this ad-hoc data can be more of a challenge than they are prepared for…enter the Data Scientist.
What is a data scientist? The term, coined in 2008, refers to a trained professional who is able to take large amounts of unstructured data, process it in different ways, and make discoveries that contribute to the overall business intelligence of a company.
Data scientists are being hired to help start-ups and established companies sort through the big data they are now able to collect, and provide real insights to make real differences. A good data scientist sees the problem, finds the data to support the solution, then builds a better mousetrap based on that collected and analyzed company data. A great data scientist finds solutions to build a better bottomline.
An example of a Data Scientist who accomplished the above, is Jonathan Goldman, of LinkedIn, who was able to take the data collected from their membership, analyze it, and figure out a new way to increase the number of accounts. Goldman used the data of user activities to test a few theories and hit on a surefire way of enticing users to increase their connections.
By incorporating this newfound formula and generating the “People You May Know” selection to user’s profiles, which yields a 30 percent clickthrough, Goldman skyrocketed activity and notably stimulated the network’s growth (read more about this story in Harvard Business Review’s article, Data Scientist: The Sexiest Job of the 21st Century).
So who makes a great Data Scientist? Right now, few university programs include Data Science as a major area of study, but some are integrating classes into existing communications, computer science and other related majors.
These students are getting a leg up in the industry, but until they graduate, companies must look for those already in the analytics space. Look for professionals with a thirst for discovery, and the ability to use data visualization tools to report findings.
While this combination may be a rarity for now, this growing field isn’t going away, and we will find more Data Scientists popping up, just as we saw Social Media Experts hit the scene three years ago.