12 Ways To Cultivate A Data-Savvy Workforce - InformationWeek

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7/7/2016
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Lisa Morgan
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12 Ways To Cultivate A Data-Savvy Workforce

Organizations aspiring to become data-driven need to take a close look at their HR practices. If your company's hiring and retention standards aren't keeping up with the times, you may be losing valuable job candidates and employees. To minimize the pitfalls of building a data-savvy workforce, consider these tips.
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Create Realistic Job Descriptions 
Many of today's data-related job descriptions are poorly conceived and written because the hiring manager, HR department, or both either don't know or can't articulate exactly what it is they need. The side effect is a job description listing far more skills than a even bona fide superhero can possibly possess. Alternatively, job decriptions may include potentially unnecessary 'requirements,' which only serve to keep away perfectly qualified candidates. 
'Keep only the most important qualifications in the posting. You'll quickly realize which skillsets can be taught, versus which are a necessity,' said Mike Stringer, co-founder of data science consulting company Datascope, in an interview. 'Some companies say Ph.D. required [or] Master's preferred, but that misses a wide array of talent. Just because a person has a Ph.D. in machine learning, doesn't mean that person will be good at your specific machine learning processes.' 
(Image: ralpoonvest via Pixabay)

Create Realistic Job Descriptions

Many of today's data-related job descriptions are poorly conceived and written because the hiring manager, HR department, or both either don't know or can't articulate exactly what it is they need. The side effect is a job description listing far more skills than a even bona fide superhero can possibly possess. Alternatively, job decriptions may include potentially unnecessary "requirements," which only serve to keep away perfectly qualified candidates.

"Keep only the most important qualifications in the posting. You'll quickly realize which skillsets can be taught, versus which are a necessity," said Mike Stringer, co-founder of data science consulting company Datascope, in an interview. "Some companies say Ph.D. required [or] Master's preferred, but that misses a wide array of talent. Just because a person has a Ph.D. in machine learning, doesn't mean that person will be good at your specific machine learning processes."

(Image: ralpoonvest via Pixabay)

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