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SEARCHING
FOR THAT
ELUSIVE DATA
SCIENTIST
INSIGHTS: “Stop Searching for
That Elusive Data Scientist” -
Michael Schrage
INSIGHT #1. Stop
hunting for that data
science unicorn and/or
silver bullet.
Odds are poor that you’ll
be able to find and hire
really good data
scientists.
• Surveys say there
simply aren’t enough
people with the unusual
blend of software skills
and statistical savvy to
go around.
• For many organizations,
a mediocre data
scientist may be worse
than none at all.
• Big organizations can
afford — or think they can
afford — to throw money at
the problem by hiring laid-
off Wall Street quants or
hiring big-budget analytics
boutiques.
• More frugal and prudent
enterprises seem to be
taking alternate
approaches.
INSIGHT #2.
Empowering small
cross-functional data-
oriented teams
• The teams must be explicitly
charged with delivering
tangible and measurable data-
driven benefits in relatively
short periods of time.
• The emphasis is on building
greater data capability than
better digital infrastructures.
• Data science must be a
cultural value, not just a
functional expertise.
• The goal is to make all of the
organization more
conversant in how to align
probability, statistics,
technology and business
value creation.
Even baby steps in analytics could yield large strides
in outcome.
“You must cultivate
internal capability, not
just hire it.”
Employing the Insights into the life of a
Manager.
Better Collection Understanding of the Employees
Better the
opportunities
to the team
Better
Relations
between the
staff.
Better learned
the workforce
will be
COST-SAVING FOR A
COMPANY
• Big savings deal for the
company by investing in small
teams, rather than hiring the
savvy quants.
• Limited ambition could do a
better job attracting credibility
and support than BHAGs.(Big
Hairy Audacious Goal)
People don’t need to
become data scientists, but
they do need to understand
and appreciate key
principles and practices of
data science.
The temporary fix of
data science teaming
doesn’t solve the
problem, but it
creates the cultural
and organizational
context for the
necessary hires to
follow.
Presented By: Charanjeet Singh Ahluwalia
Connect with me:
https://www.linkedin.com/in/charanjeet-singh-ahluwalia-
b47aa2125/

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Stop searching for elusive data scientist

  • 2. INSIGHTS: “Stop Searching for That Elusive Data Scientist” - Michael Schrage
  • 3. INSIGHT #1. Stop hunting for that data science unicorn and/or silver bullet. Odds are poor that you’ll be able to find and hire really good data scientists.
  • 4. • Surveys say there simply aren’t enough people with the unusual blend of software skills and statistical savvy to go around. • For many organizations, a mediocre data scientist may be worse than none at all.
  • 5. • Big organizations can afford — or think they can afford — to throw money at the problem by hiring laid- off Wall Street quants or hiring big-budget analytics boutiques. • More frugal and prudent enterprises seem to be taking alternate approaches.
  • 6. INSIGHT #2. Empowering small cross-functional data- oriented teams • The teams must be explicitly charged with delivering tangible and measurable data- driven benefits in relatively short periods of time. • The emphasis is on building greater data capability than better digital infrastructures.
  • 7. • Data science must be a cultural value, not just a functional expertise. • The goal is to make all of the organization more conversant in how to align probability, statistics, technology and business value creation.
  • 8. Even baby steps in analytics could yield large strides in outcome.
  • 9. “You must cultivate internal capability, not just hire it.”
  • 10. Employing the Insights into the life of a Manager.
  • 11. Better Collection Understanding of the Employees Better the opportunities to the team Better Relations between the staff. Better learned the workforce will be
  • 12. COST-SAVING FOR A COMPANY • Big savings deal for the company by investing in small teams, rather than hiring the savvy quants. • Limited ambition could do a better job attracting credibility and support than BHAGs.(Big Hairy Audacious Goal)
  • 13.
  • 14. People don’t need to become data scientists, but they do need to understand and appreciate key principles and practices of data science.
  • 15. The temporary fix of data science teaming doesn’t solve the problem, but it creates the cultural and organizational context for the necessary hires to follow.
  • 16. Presented By: Charanjeet Singh Ahluwalia Connect with me: https://www.linkedin.com/in/charanjeet-singh-ahluwalia- b47aa2125/