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The Quiet Truth about Data Science

  • Publish Date: Posted over 6 years ago
  • Author:by Niall Wharton

​It’s an extremely rare thing to watch, listen, or read something that changes not only the way you view yourself, but the way the world around you functions. Susan Cain’s “Quiet: The Power of Introverts in a world that can't stop talking” is a fantastic read that discusses the role of an introvert within a modern era. 

“The introvert/extrovert divide is the most fundamental dimension of personality. And at least a third of us are on the introverted side. Some of the world’s most talented people are introverts. Without them, we wouldn’t have the Apple computer, the theory of relativity, or Van Gogh’s sunflowers”. - Susan Cain, Quiet: The Power of Introverts in a world that can’t stop talking, 2013

Xcede are leaving no stone unturned in helping us all understand ourselves better, primarily with the aim of improving our professional strengths and weaknesses alike. Through the measurements conducted by our Learning and Development Manager, it became clear very quickly that I was quite intensely positioned at the introverted end of the personality spectrum - a ‘theorist’ and an even stronger ‘reflector’.

Insights into Cain's Book

Naturally, I was intrigued to delve into Cain’s book further after seeing our results, given that it was said to, “show how the brain chemistry of introverts and extroverts differs, and how society misunderstands and undervalues introverts. (Cain) gives introverts the tools to better understand themselves and take full advantage of their strengths.”

In a throw away comment, someone had mentioned that these traits in my character were probably caused by the fact that I have recruited within the Data Science field for over three years. Clearly, it was a comment made with tongue firmly in cheek, but actually made me think more deeply about the characteristics of those that I try to help.

Different Personality Types

Data Scientists and Data Engineers (like any other profession) across the globe have a multitude of personality types. One of the most measured and careful people that I know in the industry is a Senior Scientist at one of the most important banks in the world. Likewise, one of the real live-wires who attended our last Data Science Networking Event is a Lead Scientist at a major tech institution.

Within the Data Science recruitment space one of the frequent requests and frustrations we get from hiring managers is centred around their inability to find a Data Scientist who can also engage with clients, stakeholders and an audience. The value placed on these Data Scientists is incredible.

It’s also understandable, because Data Scientists are trying to derive insight from businesses. Someone has to be able to get the results across. Within a business context, Cain suggests that, “extroverts have taken over. Shyness, sensitivity and seriousness are often seen as being negative. Introverts feel reproached for being the way they are”. Hence, there is a common acknowledgement that Data Scientists with this type of ability, personality type, and motivation are in far shorter supply.

The Importance of Learnt Activities

A really useful and insightful piece in Cain's book describes studies that show that there is a strong direct correlation between isolated learning and skill levels in ‘learnt’ activities (coding and modelling would be prime examples of such ‘learnt’ skills). Similarly, Cain also explains that proficiency in public speaking is also something that increases with practice as a ‘learnt’ skill, and is simply not as effective when repeated in isolation (no live audience, etc).

So is the Data Science field an overwhelmingly Quiet one – and if so, is that a problem?

At this point, we’re dealing in opinions rather than fact. Things are starting to change over time – some units are choosing to share responsibilities (employing a ‘Consulting Data Scientist’ alongside their ‘Data Scientist’), whilst others elect their ‘Lead Data Scientist’ to shoulder all of these responsibilities.

Whilst there is a lot of weight placed on technical training that can be provided in companies, 

“We’ll teach you Scala!”

“We’ll teach you Spark!”

“We’ll teach you how to build deep learning frameworks that can be used for large scale object recognition with whatever tool is hot this week!”

There is a place for internal training at companies that would enable Scientists who may be introverts and not natural ‘Consultant Data Scientists’ or ‘presenters’ to improve their skills in this area and thrive in senior roles that have these responsibilities.

I’d be interested to hear your thoughts and whether you’ve had any training as a Data Scientist in these ‘softer skills’. More importantly, would this type of offer even be appealing to you in your Data Scientists job position?

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