As mentioned by Tom
Davenport few years back, Data Scientist is still a hottest job of century.
Data scientists are those
elite people who solve business problems by analyzing tons of data and
communicate the results in a very compelling way to senior leadership and
persuade them to take action.
They have the critical
responsibility to understand the data and help business get more knowledgeable
about their customers.
The importance of Data
Scientists has rose to top due to two key issues:
·
Increased
need & desire among businesses to gain greater value from their data to be
competitive
·
Over
80% of data/information that businesses generate and collect is unstructured or
semi-structured data that need special treatment
So it is extremely
important to hire a right person for the job. Requirements for being a data scientist
are pretty rigorous, and truly qualified candidates are few and far between.
Data Scientists are very
high in demand, hard to attract, come at a very high cost so if there is a
wrong hire then it’s really more frustrating.
Here are some guidelines
for checking them:
·
Check
the logical reasoning ability
·
Problem
solving skills
·
Ability
to collaborate & communicate with business folks
·
Practical
experience on collaborating Big Data tools
·
Statistical
and machine learning experience
·
Should
be able to describe their projects very clearly where they have solved business
problems
·
Should
be able to tell story from the data
· Should know the latest of cognitive computing, deep learning
I have seen smartest data
scientists in my career, who do the best job at analytics, but cannot communicate the
results to senior leaders effectively. Ideally they should know the data in
depth and can explain its significance properly. Data visualizations comes very
handy at this stage.
Today with digital
disrupting every field it has an impact on data science also.
Gartner has called this
new breed as citizen data scientists. Their primary job function is outside
analytics, they don’t know much about statistics but can work on ready to use algorithms
available in APIs like Watson, Tensor flow, Azure and other well-known tools.
The good data scientist
can make use of them to spread the awareness and expand their influence.
It has become more
important to hire a right data scientist as they will show you the results
which may make or break the company.
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