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11/15/2013
08:00 AM
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Want Big Data Success? Hire a Biologist

Not all data scientists need a math or economics background. It's time to think outside the box come hiring time.

At Catalyst, where we use big data to recruit and assemble teams for agile application development, we mix up our big data team with an in-house biologist. The mathematicians and statisticians who comprise the core of most data teams are brilliant at analyzing complex data sets, but sometimes in the messy, unstructured, imperfect social world in which we live, some of the work is to actually makes sense of this unstructured mess. Biology has lots of unstructured data, interacting in unpredictable ways. Biologists have to be comfortable with handling, dissecting, and modeling such datasets.

Genetics, and the human genome project in particular, is a great example of how many biologists effectively work as ciphers for immense but only partially understood data that they chip away at using a variety of digital data mining tools. In addition, professionals who pursue degrees in science have to write far more reports, and thereby have better communications and writing skills than mathematicians do. 

Beyond that, biologists have to think about things like epidemiology, in which tracking causes and related comorbidities is essential to determine why a disease occurred and spreads in a population, whether it's the seasonal flu infection or HIV.

Other companies have been known to hire psychologists who have the training to think critically about human behavior or philosophers who actively and skillfully conceptualize and analyze the strength of an argument and its counter-arguments. Both will interpret data from a fresh perspective. Mathematicians only analyzing data and looking for relationships can easily be misled by casual patterns.

To really drive meaningful innovation using big data, businesses need to recognize new and surprising data insights and take action on them. Having a wild card team member who has a different skill set and point of view can help provide the needed out-of-the-box perspective that may just turn big data into business innovation.

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Yukon
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Yukon,
User Rank: Apprentice
11/19/2013 | 3:09:38 PM
support to the biologists
I have had some exceptional students from the conservation biology Ph.D. program in my graduate level regression class.  Although their statistics backgrounds tend to be weaker than those of our own statistics students, they make up for it with an excellent study ethic (data collection in the Florida swamps as an arduous alternative), an appreciation for temporal and spatial variables (not just generic X's as predictor variables), an inherent grasp of hypotheses and tentative models, and considerable experience in documenting their work.  These students are certainly experienced at writing reports and explaining the results in a fashion understandable to the general public (goes with the conservation biology territory I guess).   Finally, those students who have collected data themselves in the field, have a healthy appreciation and skepticism for the examples presented in class.
Alison Diana
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Alison Diana,
User Rank: Moderator
11/19/2013 | 9:53:00 AM
Creativity Key
Many folks I speak to say they look for creative people, folks with liberal arts degrees and natural curiousity. While these people can learn big data, their inherent skills will provide them with the keys to success within big data careers. I thought this was interesting, since liberal arts degrees have been panned for so long. 
Laurianne
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Laurianne,
User Rank: Author
11/18/2013 | 10:16:52 AM
Re: Big Data what?
I like the hire a 'wild card' advice here. Some of the smartest CIOs will tell you when you hire, you must find people who are not just like you -- otherwise you will just listen to yourself talk, no one will challenge your ideas. You need diversity of experience in IT teams. In this age of big data, that is only more true. I hope hiring managers will think outside the box a bit. IT hiring has become too bogged down looking for exact matches to crazy requirements lists, don't you think?
BethSchultz
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BethSchultz,
User Rank: Apprentice
11/18/2013 | 10:16:34 AM
Re: Outside the box
@Shane, I agree that this is spot-on advice. To be effective, a data science team working with big data needs people who can do the math and know the computer science and create the models, but the results of their work will only be as good as their ability to communicate them to the business. That's where the insight and innovation that non-traditional data analysts can bring to the team really shine.
Kim Davis
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Kim Davis,
User Rank: Apprentice
11/15/2013 | 4:39:28 PM
Re: Big what?
Big data is vague (how big?), and also non-specific (the challenges of analysing vast quantities of numerical data on one server are different from those of analysig unstructured data dispersed over a number of servers): but I fear we're stuck with the term.
Thomas Claburn
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Thomas Claburn,
User Rank: Author
11/15/2013 | 1:43:17 PM
Big what?
I'm hoping we can get past the term "big data" and move to something more specific. 
Shane M. O'Neill
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Shane M. O'Neill,
User Rank: Author
11/15/2013 | 9:04:17 AM
Outside the box
This is spot on. People from all lines of work are interested in the stories data can tell and the insights and business results it can produce. If we leave all data analysis up to traditional mathematicians and statisticians, we may not see the big picture. 
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