“This push for restructuring the workforce to be data savvy can
be observed in various departments of an organization.”
Prof. Kurnicki’s
latest book, Learn
R by Coding, is a
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students or anyone
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An enduring education
Use your lifelong learning elective to
upskill in emerging areas in business. If
you’re looking to really future-proof your
career, a Masters in Business Analytics
includes core courses in programming
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All of these revolutionary or evolutionary workforce
changes are based on explanatory and predictive data
analysis. This is the main reason why the future of work
will be largely defined by trends in data science.
On one hand, we have industries that historically re-
lied on “muscle work.” With the 3rd and 4th industrial
revolutions, the “muscle work” was optimized to a point
where it could be replaced with machines or comput-
ers. Nowadays, these industries are heading toward
a full replacement of a human worker with humanoids
and robots.
The main role of data science in the process of hu-
manoidization (replacing humans with humanoids) is to
optimize business objectives. A data scientist’s main
goal is to find an objective function, such as maximizing
produced units or minimizing the time spent on build-
ing a product. Once the objective function is defined,
the data scientist writes an optimization algorithm that
gives a set of optimal parameters. These optimal param-
eters can be used to calibrate machines such as a pro-
duction line robot or a seabed driller.
On the other hand, there are industries that rely on
“intelligent work” and human creativity such as banking,
education, and medical services. In this workspace, hu-
mans can rest assured that they won’t be replaced any-
time soon. However, this workspace is adapting to new
business needs and is forcing employees to change the
way they think, collaborate, and execute. People are ex-
pected to optimize their workflow and be more efficient.
Many Fortune 500 companies are educating all
their staff in programming languages such as Python or
R (just like they did with MS Excel 20 years ago), so that
they can automate their work, spend less time running
old processes or business-as-usual tasks, and focus
their efforts on creating data-driven solutions.
This push for restructuring the workforce to be data
savvy can be observed in various departments of an
organization, especially sales, marketing, finance, and
human resources, and is due to the fact that more data
is being collected and made available. Business leaders
know that data-optimized solutions are more effective,
cheaper, and easier to measure and should be focused
on changing the future workforce in a way that focuses
on data.
The future of work lies in data science.
Prof. Thomas Kurnicki is a data and analytics consultant, Hult alum,
and data science and programming professor in Hult’s Masters in
Business Analytics program. He has worked for Wells Fargo and
CBRE in San Francisco, been involved in venture capital in Silicon
Valley with Keiretsu Capital, and has co-founded two companies in
his native Poland. Thomas is focused on implementing quantitative
solutions in the investment management industry. He’s passionate
about implementing data-focused projects in fields and industries
that are on the verge of technological disruption.
Faculty
Industrial
Revolution
Fads and trends may come and go, but industries weather the change. The giants
of global commerce are working hard and fast to ensure they are future-
proofed in an unpredictable climate. Take a look under the hood of three
veteran sectors—automotive, fashion, and finance—and meet the inspiring
alumni on the cutting edge.
Changing Industry
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