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STOP SEARCHING FOR
THAT ELUSIVE DATA
SCIENTIST
Stop searching for that elusive data scientist
DATA SCIENTIST- NOT COMPULSORY!!
WHAT IS TO BE DONE?
• People don’t need to become data scientists, but
they need to understand and appreciate key
principles and practices of data science.
• We need extensive, but not exhaustive, exercises in
simple data science and analytics.
Stop searching for that elusive data scientist
Stop searching for that elusive data scientist
Stop searching for that elusive data scientist
• A typical team maybe collectively less
skilled and competent than a typical data
scientist. But a collective team learns from
each other and sends a message to the rest
of the organization that even baby steps in
analytics could yield large strides in
outcome.
SO ARE THESE TEAMS ULTIMATELY A
SHORT-TERM FIX RATHER THAN A
MORE SUSTAINABLE SOLUTION TO THE
DATA SCIENTIST SHORTAGE?
• Smart organizations
would be foolish to
outsource this away from
the very people who need
to be more data-driven.
• You want to cultivate internal
capability, not just hire it.
• That’s why a team is a good starting
point!
MANAGERS :
•Give up!
• Stop hunting for that data science unicorn and/or
silver bullet
Stop searching for that elusive data scientist
RATHER,
• The accent is on the word team; the emphasis
is on building greater data capability than
better digital infrastructures. The goal is to
make all of the organization — not just the
geeks and quants — more conversant in how
to align probability, statistics, technology and
business value creation.
• A cultural and organizational context for the
necessary hires to follow is the profit.
Sometimes the data show that “buying time”
the right way can be a terrific investment.
THANK YOU!!

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Stop searching for that elusive data scientist

  • 1. STOP SEARCHING FOR THAT ELUSIVE DATA SCIENTIST
  • 3. DATA SCIENTIST- NOT COMPULSORY!!
  • 4. WHAT IS TO BE DONE? • People don’t need to become data scientists, but they need to understand and appreciate key principles and practices of data science. • We need extensive, but not exhaustive, exercises in simple data science and analytics.
  • 8. • A typical team maybe collectively less skilled and competent than a typical data scientist. But a collective team learns from each other and sends a message to the rest of the organization that even baby steps in analytics could yield large strides in outcome.
  • 9. SO ARE THESE TEAMS ULTIMATELY A SHORT-TERM FIX RATHER THAN A MORE SUSTAINABLE SOLUTION TO THE DATA SCIENTIST SHORTAGE?
  • 10. • Smart organizations would be foolish to outsource this away from the very people who need to be more data-driven. • You want to cultivate internal capability, not just hire it. • That’s why a team is a good starting point!
  • 11. MANAGERS : •Give up! • Stop hunting for that data science unicorn and/or silver bullet
  • 13. RATHER, • The accent is on the word team; the emphasis is on building greater data capability than better digital infrastructures. The goal is to make all of the organization — not just the geeks and quants — more conversant in how to align probability, statistics, technology and business value creation.
  • 14. • A cultural and organizational context for the necessary hires to follow is the profit. Sometimes the data show that “buying time” the right way can be a terrific investment.