In the hunt for a few good data scientists -- actually, hopefully, many
good data scientists -- a group of leading universities, foundations
and the U.S. government are investing in efforts to promote this
emerging profession.
The new five-year, $37.8 million initiative, with support from the Gordon and Betty Moore Foundation and Alfred P. Sloan Foundation, was announced at a meeting sponsored by the White House Office of Science and Technology Policy. The partnership includes New York University, the University of California, Berkeley and the University of Washington, and it is hoped the effort will spur collaborations within and across the three campuses and other partners pursuing similar data-intensive science goals.
The program seeks to encourage cross-disciplinary interactions between data scientists and other fields, such as astrophysics, genetics, or economics. In addition, organizers hope to establish and highlight data scientist career paths that will attract more talented individuals.
Data scientists aren't the only professionals in demand in today's big data-intensive space. Enterprises need a range of big data management and analysis skills. Recently, InformationWeek's Jeff Bertolucci outlined five key big data areas in demand across today's organizations:
1) Data evangelist. Doesn't require data scientist skills, but rather, "expertise in a specific business area, as well as a curious nature and a knack for finding new business uses for big data."
2) Contextual analyst. Requires understanding of "the meaning of data, particularly as its relevance and importance evolves, something today's algorithmic models aren't very good at."
3) Data visualizer. These are the folks that are able to take big data and provide an easy-to-grasp presentation to users -- in a very graphical way.
4) Data custodian. The "caretaker of the organization's data" -- a position that takes the role of database administrator to the next level.
5) Neuro-analyst. This futuristic-sounding role is likely assigned to a neurobiologist "who understands how cognition works, and how an organization can develop strategies to present data in ways that people can easily grasp." Mixing data science with human nature.
(Photo: University of Maryland Media Relations.)
The new five-year, $37.8 million initiative, with support from the Gordon and Betty Moore Foundation and Alfred P. Sloan Foundation, was announced at a meeting sponsored by the White House Office of Science and Technology Policy. The partnership includes New York University, the University of California, Berkeley and the University of Washington, and it is hoped the effort will spur collaborations within and across the three campuses and other partners pursuing similar data-intensive science goals.
The program seeks to encourage cross-disciplinary interactions between data scientists and other fields, such as astrophysics, genetics, or economics. In addition, organizers hope to establish and highlight data scientist career paths that will attract more talented individuals.
Data scientists aren't the only professionals in demand in today's big data-intensive space. Enterprises need a range of big data management and analysis skills. Recently, InformationWeek's Jeff Bertolucci outlined five key big data areas in demand across today's organizations:
1) Data evangelist. Doesn't require data scientist skills, but rather, "expertise in a specific business area, as well as a curious nature and a knack for finding new business uses for big data."
2) Contextual analyst. Requires understanding of "the meaning of data, particularly as its relevance and importance evolves, something today's algorithmic models aren't very good at."
3) Data visualizer. These are the folks that are able to take big data and provide an easy-to-grasp presentation to users -- in a very graphical way.
4) Data custodian. The "caretaker of the organization's data" -- a position that takes the role of database administrator to the next level.
5) Neuro-analyst. This futuristic-sounding role is likely assigned to a neurobiologist "who understands how cognition works, and how an organization can develop strategies to present data in ways that people can easily grasp." Mixing data science with human nature.
(Photo: University of Maryland Media Relations.)
This post was originally published on Smartplanet.com
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