Harvard Business Review has recently selected the role of data scientist as the sexiest job of the 21st century. The award is the business world’s equivalent of People Magazine’s annual Sexiest Man Alive designation.
But who could ever have imagined that the nod would go to the data scientist, a role pioneered by the world’s Web behemoths and now being sought after by mainstream companies seeking to gain actionable business insight from sifting through large volumes of data?
While the definitions of a date scientist are still evolving, one common denominator is that data scientists help companies make money analyzing data. Take, for example, Jonathan Goldman, who, while working at LinkedIn, began forming theories about what could happen by tapping into analytics to link user profiles.
Goldman, however, is overlooked by the company’s engineering team and he’s dismissed by colleagues who doubt why anyone would need LinkedIn to figure out their networks for them. Nonetheless, Goldman still charges ahead with his idea – an idea that has resulted in the company’s popular and profitable “people you may know” feature.
The sudden demand for data scientists like Goldman is the result of companies struggling to corral the data flowing into their networks in multiple varieties and formats and in unprecedented volumes, according to HBR.
“If your organization stores multiple petabytes of data, if the information most critical to your business resides in forms other than rows and columns of numbers, or if answering your biggest question would involve a ‘mashup’ of several analytical efforts, you’ve got a big data opportunity,” according to HBR.
But what characteristics do data scientists share?
- They unearth business insight from large data sets.
- They make analysis possible by bringing structure to large amounts of unstructured data like Web data, call center notes, social networking information and other data that can’t be easily analyzed in a database.
- They are adept at communicating what they glean from the analysis and how it can impact the business.
Most notably, data scientists “help decision makers shift from ad hoc analysis to an ongoing conversation with data,” according to HBR.
At PayPal, for example, Chief Scientist Mok Oh is analyzing data – such as what product a customer looks at before or after making a purchase – to formulate strategies to bolster sales.
“Knowing the right question, or problem to solve is very important,” Oh told Forbes. “Sometimes the computer scientists are [pressed into service as] data scientists. But computer scientists are not trained to ask the right business questions. They might be asking some other cool questions that will help them with research or publication, but not necessarily the right questions to ask for the business.”
Despite their potential to help businesses hone strategy based on data, data scientists can be hard to find. McKinsey Global Institute predicts that demand for data scientists will exceed supply by as much as 190,000 by 2018 if current trends hold. In addition, companies will need 1.5 million more managers and business analysts to formulate the questions and make decisions based on the analytical outcomes that are generated by data scientists, according to McKinsey.
HBR shares several tips for finding data scientists:
- Focus recruiting at universities like Stanford, MIT, Berkeley, Harvard, Carnegie Mellon, North Carolina State, UC Santa Cruz, the University of Maryland, the University of Washington, and UT Austin
- Look for them on LinkedIn
- Find talented data scientists among those who enter coding competitions on Kaggle or TopCoder
- Look for people who can find a story in data and effectively tell that story to executives
- Attend industry conferences that may attract data scientists
- Make sure a candidate’s business chops are equal to his quant skills
Next Steps:
- Please join us on Tuesday, March 5th, 2013, at 11 a.m. EST, for our complimentary webcast, “Data Science 2.0: Guided and In-line Analytics with Spotfire.” In this webcast, Michael O’Connell, PhD., Sr. Director Analytics, TIBCO Spotfire, will describe how Spotfire enables Data Detectives across the business and analyst communities – uncovering insights across a broad set of industry applications.
- Subscribe to our blog to stay up to date on the latest insights and trends in big data and the role of the data scientist.
Heather Harreld
Spotfire Blogging Team
