To be or Not to be: A Data Scientist?

Posted in Lending Articles By Fedrick William - Jul 11,2019
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You might have come across the novel profession of a data scientist in your professional/student life. In a world where data is the new oil and currency, it is not surprising that the profession of a data scientist has caught everyone’s attention.

So then, who is a data scientist (DS)?  Is this profession just a fad of the digital world or does this profession carry some weight?

A combination of traits that exist in mathematicians, computer scientists and trend-spotters, Data Scientists are a new breed of professionals that juggle between IT and business. They are data analysts who use technical skills to bring solutions to complex problems.

Let’s have a look at the traits that a Data Scientist should possess and certain biases you should be cognizant about. This would be helpful if you are already a self-proclaimed data scientist or are considering going down that road or even if you are just inquisitive about the work of a DS.

If you have noticed, I have used the word trait (and not skill). While most use these two terms interchangeably, it isn’t really accurate. While there does exist a relationship between the two, perhaps even some overlap, but the core concepts are different.

Data Scientist



1. Is Task-Oriented
2. Is Experienced Based
3. Is a Continuous Process
1. Is Character Oriented
2. Are integral to a person
3. Is Relatively Constant

A data scientist has to be good with both words and numbers. When we come across, say a news story, it seems more authentic when there are numbers and figures involved. But emotions are only evoked through the story. Data Scientists are in a way, constantly digging for such stories that can explain various functions, across a variety of fields, from management to psychology to population.

Here are a few more traits of a Data Scientist –

  1. Has a feeling for numbers
  2. Likes to experiment
  3. Is inquisitive
  4. Is a responder and not a reactor
  5. Is a storyteller

Let’s look at each of these traits in detail:

Feeling for Numbers Likes to Experiment Inquisitive Responder Story Teller
Aggregates and breaks down numbers



Always looks for actionable insights


Statistics (Extremely critical for Modelling)

Open to learning new tools and techniques




SQL, SAS, R, Python, SSPS, Excel, Big Data Tools, Excel



Hypothesis Testing, Correlation, Pareto, Linear Regression, Logistic Regression, Clustering Methods…the list can go on.



Has the ability to choose the weapon of choice strategically for the problem at hand.

The person who always starts with the WHY?



Why are we undertaking this analysis?


Why are we making this change?


Has an extremely   disposition






Doesn’t break down under pressure



Believes in facts (not opinions)


Analyses the numbers before passing any inferences


Backs up their statements with data (As Deming said, ‘In God, we trust, all others must bring Data’)


Doesn’t feel the need to win every battle, but definitely has the vision to win the war.

This trait is NOT merely an icing on the cake. This trait completes a DS.



The ability to draw people to the problem statement in a prosaic yet indulgent manner


To be a good storyteller, one also needs to be inspired. My guess is that a reader generally has a higher chance of being a good storyteller!

Armoured with this understanding, I would like to sign off with one of Deming’s classic maxims, “Without data you are just another person with an opinion

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