A recent Deloitte Press article discusses a role that is becoming more and more important as a result of the explosion of big data and data science in industry. The article In praise of “light quants” and “analytical translators” discussed the important role of analtyical translators, which may be even harder to find than actual data scientists themselves.
“When we think about the types of people who make analytics and big data work, we typically think of highly quantitative or computational folks with hard knowledge and skills. You know the usual suspects: data scientists who can make Hadoop jump through hoops, statisticians who dream in SAS or R, data wizards who can extract two years of data from a medical device that normally dumps it after 20 minutes (a true request)....A “light quant” is someone who knows something about analytical and data
management methods, and who also knows a lot about specific business
problems. The value of the role comes, of course, from connecting the
Actually, in some of my previous ponderings and speculations about the coming convergence of big data, analytics, and genomics, I discussed the potential for such a role in the precision agriculture and data science space (See Big Data: Causality and Local Expertise Are Key in Agronomic Applications):
"as we think about all the data that can potentially be captured through
the internet of things from seed choice, planting speed, depth,
temperature, moisture, etc this could become especially important. This
might call for a much more personal service including data savvy reps to
help agronomists and growers get the most from these big data apps or
the data that new devices and software tools can collect and aggregate.
Data savvy agronomists will need to know the assumptions and nature of
any predictions or analysis, or data captured by these devices and apps
to know if surrogate factors like Dan mentions have been appropriately
considered. And agronomists, data savvy or not will be key in
identifying these kinds of issues. Is there an ap for that? I don't
think there is an automated replacement for this kind of expertise, but
as economist Tyler Cowen says,
the ability to interface well with technology and use it to augment
human expertise and judgement is the key to success in the new digital
age of big data and automation. "
In fact, I recently discovered an actual position for a major player in this space with the title "BioAg Knowledge Transfer Agronomist" that seems to fit the bill. I think we will see more roles like this in the future.
Farm Link: The Rise of Data Science in Agriculture http://econometricsense.blogspot.com/2015/06/farmlink-and-rise-of-data-science-in.html
The Internet of Things, Big Data, and John Deere http://www.econometricsense.blogspot.com/2015/01/the-internet-of-things-big-data-and.html
The Use of Knowledge (in a) Big Data Society http://ageconomist.blogspot.com/2015/07/the-use-of-knowledge-in-big-data-society.html