Data scientist may be the hot job of 2013, but many data professionals report they are already doing much of the work that would be defined as the data scientist role. They just aren’t calling themselves data scientists – at least not yet.

In a new survey of 199 data managers I conducted as part of my work with Unisphere Research and Information Today, Inc., we found that the traits of data scientists – individuals whose backgrounds include IT and programming; math and statistics; and a willingness to look at things differently—are already seen within today’s organizations, in the day to day work performed by database administrators, analysts, managers and consultants. The survey was conducted among members of the Independent Oracle Users Group.

The study, available from the IOUG website, finds that increasingly, the jobs of all these professionals encompass data scientist-style activities—taking raw data sets, and finding ways to extract the nuggets of information of value to the business.

Ironically, only one respondent in the entire survey actually had the title of “data scientist.” The most common job titles reported include database administrator (37%), CIO or vice president of IT (19%), data, business intelligence, or data warehouse architects (7%), and IT consultants or systems integrators (7%). While virtually none of the respondents would go as far as saying that they are have the actual title of data scientist, they are, for all intents and purposes, fulfilling that role. It’s also notable that 12% of respondents already consider themselves to be data scientists. In addition, 13% say their jobs will be moving in this direction over the next one to two years, while 25% say they eventually will be taking on data scientist roles.

While no one had the title of data scientist, the top activities on the rise as a part of respondents’ jobs read like a job description for this emerging role:

1. Communicate/”tell a story” with data
2. Work with end users to determine information requirements in new or modified systems
3. Translate business needs into analytic and reporting requirements
4. Maintain or participate in cross-functional teams or data center of excellence
5. Oversee or guide enterprise application integration
6. Filter and organize data
7. Manage data storage/retrieval
8. Design procedures for the solutions of business problems
9. Enable forecasting and prediction
10. Oversee or advise on systems design and analysis
11. Mine data for patterns
12. Capacity planning
13. Develop analytic models
14. Run and analyze test applications or algorithms
15. Apply or create advanced algorithms