From the course: Predictive Analytics Essential Training for Executives
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Data science job requirements and problems they can create
From the course: Predictive Analytics Essential Training for Executives
Data science job requirements and problems they can create
- Hiring in data science is broken. Demand is high but so is turnover. The joke for a while was that there was a job posting that wanted five years of R, five years of Python and five years of TensorFlow. Well, at the time that I first heard the joke, TensorFlow had only been out for two years. So it's pointless to talk about specific technologies because a year from now, the list might change a bit. And that's really the point. Hiring a diverse team is your best bet and that means a variety of experience. One particular client talked at length about their extensive Python grammar exam given to applicants before they could apply. Don't get me wrong, thinking like a programmer can be an important skill but too much emphasis on the details of a particular technology option can warp your team. I asked my client if they would get excited about a 40-year-old with 10 or more years of industry experience that had learned on…
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Contents
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Data science job requirements and problems they can create3m 16s
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Growing a data science team organically1m 52s
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Data scientists both with and without vertical industry experience1m 48s
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The importance of subject matter expertise to modeling2m 16s
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CRISP-DM: Established process of producing predictive models5m 16s
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Traits of top performing data scientists3m 25s
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