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Analytics: A Gap in the Market or a Market in the Gap?
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Re: Data Science Gap
  • 1/29/2015 3:37:31 PM
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@Jim, OUCH - that was not good. And your feelings at that discovery mirror those of every manager who thought that they were getting a desired resource but discovered they were not getting what they paid for. That's why in contracting, labor categories usually have levels (like analyst 1, analyst 2, etc.). That resource might have the desired label but how close s/he approximates the label is based on which level you want to pay.

Re: Data Science Gap
  • 1/29/2015 3:25:59 PM
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@Bkbeverly. You laugh about putting the "corn" label on a can of peas. I once opened up a can of green beans only to find corn inside.

Re: Data Science Gap
  • 1/29/2015 12:41:00 PM
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Maryam - agreed - focus should be on the skill set. If you can do the work then the title will follow and not the reverse. It like putting the label CORN on a can of peas and hoping the peas will turn into corn (SMILE).

Re: Data Science Gap
  • 1/28/2015 4:35:31 PM
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Bryan I have to agree the danger with en vogue titles is that they fall out of vogue just as easily. Focusing on the skill set of a data scientist I believe is a more evergreen career focus and will yield better career results long term.

Re: Data Science Gap
  • 1/28/2015 3:41:05 PM
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Terry - that is the issue. Who is saying the value of data scientists is increasing - the software and training vendors or the market place? Until non-cash compensation like health care costs freeze, it is unlikely that one will get significantly more money and employer health care coverage. Also even if the market demand does increase, it is cheaper to retrain a gifted and talented employee than to recruit someone - especially since there are not any data scientists out there with 20 years of experience.

Re: Data Science Gap
  • 1/28/2015 10:50:33 AM
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Seth, good point about using things like SQL and R on a regular basis. I'm sure there are hiring companies that would look at those skills as checkboxes on a candidate's application. However, smart companies want to see that you have some real experience in the languages and tools that you've learned.

Re: Data Science Gap
  • 1/27/2015 12:53:39 PM
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It's a sure bet that industry management folks will try to get talent at the least possible pay point. Making up new titles most likely results in a deflation of pay and benefits for the holders of those titles. As pointed out, if you can get an employer to pay for training, you're probably better off instead of upgrading your training for a gamble at higher paychecks.

Re: Data Science Gap
  • 1/26/2015 11:12:56 PM
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I wouldn't hold my breath, Seth. Where there's title inflation, there's salary deflation. Maybe since analytics is becoming more valuable, these data scientists will get a nice $ bump.

Re: Data Science Gap
  • 1/26/2015 10:55:13 PM
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@ Terry, hopefully the title will come with a big pay raise.  Like anything, it isn't enough to learn SQL or R,, but one has to use it on a regular basis.  If one's current job doesn't entail that, that is another challenge. 

Re: Data Science Gap
  • 1/26/2015 4:05:32 PM
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Jim, agreed. I used to be a VisiCalc guru (http://en.wikipedia.org/wiki/VisiCalc) until some package called Lotus 1-2-3 came out ... (SMILE) Unfortunately the rate of technological change means that one has a limited window to ramp up on a new skill and get some career growth out of it - until the next thing comes along. If you were trained in BMDP, SPSS and SAS during the last 30 years, then R, STATA and matrix programming will be required learning unless there is enough work out there for you to make it with current skill sets. I have found it good to ask employers to pay for training; makes the cost/benefit ratio a whole lot better in case the income benefits are small.

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