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An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

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The Challenges of Hiring Artificial Intelligence Professionals

A human resource perspective

David Chong
TDS Archive
Published in
5 min readDec 20, 2019

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I was speaking to my manager the other day over coffee and the conversation steered towards the topic of Artificial Intelligence (AI). While on that topic, he commented that, “In the field of AI, many people talk but don’t deliver”. While what he said was true in general, I feel that success or failure of AI projects are predetermined at the point of hiring.

The rich get richer, the poor get poorer

Over the past few months, I have been interviewing with various firms across different industries for data analyst, junior data scientist or AI engineer positions. While interviewing, I noticed many differences between these companies I interviewed for. They can be classified into two categories: AI Leaders and the AI Laggards.

Source from Accenture: The Momentum Mindset [1]

There also exists a ‘rich get richer, poor get poorer’ phenomenon, and the rationale for this is simple.

Before I jump into that, we need to segregate two groups of individuals:

The Amateurs

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TDS Archive
TDS Archive

Published in TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

David Chong
David Chong

Written by David Chong

Software Engineer @ Shopee; Closet n3rd; Husband & Father; LinkedIn → bit.ly/3CmUbUf; Medium — tinyurl.com/2rk9ub8k; Support me → tinyurl.com/davidcjw

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