The Harvard Business Review
claims as much. 'Data scientist' seems like a catch-all marketable title that many quantiative researchers can fall under if you're speaking to someone outside of academia. As a computational biologist, I will vouch for HBR and tell you they definitely hit home with several observations in this article. Here's a bit of what 'data scientists' can do:
More than anything, what data scientists do is
make discoveries while swimming in data. It’s their preferred method of
navigating the world around them. At ease in the digital realm, they are
able to bring structure to large quantities of formless data and make
analysis possible. They identify rich data sources, join them with
other, potentially incomplete data sources, and clean the resulting set.
Why they do it:
The data scientists we’ve spoken with say they
want to build things, not just give advice to a decision maker. One
described being a consultant as “the dead zone—all you get to do is tell
someone else what the analyses say they should do.” By creating
solutions that work, they can have more impact and leave their marks as
pioneers of their profession.
And how they like to do things:
Data scientists don’t do well on a short leash.
They should have the freedom to experiment and explore possibilities.
That said, they need close relationships with the rest of the business.
The most important ties for them to forge are with executives in charge
of products and services rather than with people overseeing business
functions. As the story of Jonathan Goldman illustrates, their greatest
opportunity to add value is not in creating reports or presentations for senior executives but in innovating with customer-facing products and
processes.
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