Why Is Finding Data Scientists So Hard?


Why Is Finding a Data Scientist So Hard?

You feel it. You may even experience it on a daily. But you may not know just how big the talent gap is exactly.  When it comes to finding qualified data scientists, data engineers, or machine learning engineers, the reality of supply and demand is stark.

Spurred by exponential increases in data and significant improvements in computing power, data science exploded in the last few years. Increased technology adoption only added to our data generation. It also changed the way we shop, do business, bank, and even the way we work — just to mention a few examples.  Digitalization and technology adoption only added more to the heaps of data we all have been generating.  But data is only truly useful if it is kept, organized in a clean and efficient way for interpretability. 

The number of open positions in the United States grossly outweighs the number of qualified individuals suited for these jobs. Why is that? Businesses across various industries recognize they can glean valuable insights from data and they can use these insights to develop new, better solutions to get ahead of competition.  AI solutions today have the potential to change the way we do business entirely. 

As industry data sources show, all these factors just cause demand for these skills to climb higher and higher with no signs of slowing down: 

  • Data scientist jobs increased 37% annually
  • Demand for data scientists is predicted to increase by 30-35% by 2023
  • While AI and machine learning engineers jobs grew 74% annually in the last 4 years

If your product roadmaps and business strategies rely on skilled data scientists, AI and machine learning engineers, and you can’t afford to stall those, you should consider looking outside of traditional sources for that critical talent.  

Finding data scientists

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