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Getting Started in ‘Big Data’ - The CFO Report - WSJ
February 4, 2014 | WSJ |by JAMES WILLHITE.

executives and recruiters, who compete for talent in the nascent specialty, point to hiring strategies that can get a big-data operation off the ground. They say they look for specific industry experience, poach from data-rich rivals, rely on interview questions that screen out weaker candidates and recommend starting with small projects.

David Ginsberg, chief data scientist at business-software maker SAP AG , said communication skills are critically important in the field, and that a key player on his big-data team is a “guy who can translate Ph.D. to English. Those are the hardest people to find.”

Along with the ability to explain their findings, data scientists need to have a proven record of being able to pluck useful information from data that often lack an obvious structure and may even come from a dubious source. This expertise doesn’t always cut across industry lines. A scientist with a keen knowledge of the entertainment industry, for example, won’t necessarily be able to transfer his skills to the fast-food market.

Some candidates can make the leap. Wolters Kluwer NV, a Netherlands-based information-services provider, has had some success in filling big-data jobs by recruiting from other, data-rich industries, such as financial services. “We have found tremendous success with going to alternative sources and looking at different businesses and saying, ‘What can you bring into our business?’ ” said Kevin Entricken, the company’s chief financial officer.
massive_data_sets  analytics  data_scientists  cross-industry  recruiting  howto  poaching  plain_English  connecting_the_dots  storytelling  SAP  Wolters_Kluwer  expertise  Communicating_&_Connecting  unstructured_data  war_for_talent  talent  PhDs  executive_search  artificial_intelligence  nontraditional 
june 2014 by jerryking

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