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1 of 16
THE ELUSIVE DATA
SCIENTIST
2
HELLO!
I AM ROHIT KAR
I am an Electrical Engineering
student
You can find me at
rohit.kar96@gmail.com
3
THE PROBLEM OF
FINDING THE IDEAL
DATA SCIENTIST
“
Based purely on the data, a really good data scientist
will probably tell you the odds are poor that you’ll be
able to find and hire really good data scientists.
-Michael Schrage
5
▪ Surveys reveal the scarcity of data scientists
▪ Not enough people with the usual blend of software
skills and statistical knowledge
▪ Creating a vacuum
▪ Incomplete knowledge is dangerous
6
Scarcity of Data Scientists
BIG
CONCEPT
Bring the attention of your
audience over a key concept
using icons or illustrations
7
Companies should stop
hunting for data scientist and
spend valuable resources
searching for the right analyst
in the immediate future
Two key Insights
Companies should focus on
creating small teams not
addressing big problems but
to generate insights that could
get the company doing
something interesting really
fast
8
Hunt for Data Scientist
▪ There is a shortage of data scientist in the
industry
▪ Organizations can’t take full advantage of
their capabilities
▪ Spending money on wall-street quants to
do the job of data scientist is not efficient
▪ Little knowledge is data-dangerous
9
USING SMALL TEAMS
10
● Seed fund an empower small cross-functional and data-oriented teams
● They are charged with producing data-driven insights in short periods of
time
● The goal is to make all of the organization more conversant with the
tools of probability and statistics
● Not aimed at solving big and grand challenges
● But focusing on generating insights that could get the company doing
something interesting really fast
IN TWO OR THREE COLUMNS
Yellow
Is the color of gold,
butter and ripe
lemons. In the
spectrum of visible
light, yellow is found
between green and
orange.
Blue
Is the colour of the
clear sky and the deep
sea. It is located
between violet and
green on the optical
spectrum.
Red
Is the color of blood,
and because of this it
has historically been
associated with
sacrifice, danger and
courage.
11
HOW ARE THESE INSIGHTS
HELPFUL TO
MANAGERS?
12
13
● There is a shortage of data scientists
● Managers should make wise use of their limited resources
● They should not hire the laid off wall-street quants to do the job of a
data scientist
● Hiring people with limited knowledge of statistics and probability and
limited software skills can be data-dangerous
● This can lead to wrong decision making and skewed judgements
WISE USE OF RESOURCES
DATA LITERATE TEAMS
14
● Create small teams working to produce insights that help the company do
something interesting really fast
● Make the entire organization more conversant in the tools of data analytics
● Even baby steps in analytics could produce large strides in outcome
CLOSING OFF
People do not need to become data scientist, but they need to
understand the key principles of statistics and data analysis. Although the
temporary fix of data science teaming does not solve the problem, but it
creates the cultural and organizational context for necessary hires to
follow.
15
16
THANKS!
ANY QUESTIONS?

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Week3 day2slide

  • 2. 2
  • 3. HELLO! I AM ROHIT KAR I am an Electrical Engineering student You can find me at rohit.kar96@gmail.com 3
  • 4. THE PROBLEM OF FINDING THE IDEAL DATA SCIENTIST
  • 5. “ Based purely on the data, a really good data scientist will probably tell you the odds are poor that you’ll be able to find and hire really good data scientists. -Michael Schrage 5
  • 6. ▪ Surveys reveal the scarcity of data scientists ▪ Not enough people with the usual blend of software skills and statistical knowledge ▪ Creating a vacuum ▪ Incomplete knowledge is dangerous 6 Scarcity of Data Scientists
  • 7. BIG CONCEPT Bring the attention of your audience over a key concept using icons or illustrations 7
  • 8. Companies should stop hunting for data scientist and spend valuable resources searching for the right analyst in the immediate future Two key Insights Companies should focus on creating small teams not addressing big problems but to generate insights that could get the company doing something interesting really fast 8
  • 9. Hunt for Data Scientist ▪ There is a shortage of data scientist in the industry ▪ Organizations can’t take full advantage of their capabilities ▪ Spending money on wall-street quants to do the job of data scientist is not efficient ▪ Little knowledge is data-dangerous 9
  • 10. USING SMALL TEAMS 10 ● Seed fund an empower small cross-functional and data-oriented teams ● They are charged with producing data-driven insights in short periods of time ● The goal is to make all of the organization more conversant with the tools of probability and statistics ● Not aimed at solving big and grand challenges ● But focusing on generating insights that could get the company doing something interesting really fast
  • 11. IN TWO OR THREE COLUMNS Yellow Is the color of gold, butter and ripe lemons. In the spectrum of visible light, yellow is found between green and orange. Blue Is the colour of the clear sky and the deep sea. It is located between violet and green on the optical spectrum. Red Is the color of blood, and because of this it has historically been associated with sacrifice, danger and courage. 11
  • 12. HOW ARE THESE INSIGHTS HELPFUL TO MANAGERS? 12
  • 13. 13 ● There is a shortage of data scientists ● Managers should make wise use of their limited resources ● They should not hire the laid off wall-street quants to do the job of a data scientist ● Hiring people with limited knowledge of statistics and probability and limited software skills can be data-dangerous ● This can lead to wrong decision making and skewed judgements WISE USE OF RESOURCES
  • 14. DATA LITERATE TEAMS 14 ● Create small teams working to produce insights that help the company do something interesting really fast ● Make the entire organization more conversant in the tools of data analytics ● Even baby steps in analytics could produce large strides in outcome
  • 15. CLOSING OFF People do not need to become data scientist, but they need to understand the key principles of statistics and data analysis. Although the temporary fix of data science teaming does not solve the problem, but it creates the cultural and organizational context for necessary hires to follow. 15