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What Are the Soft Skills that Data Scientists Need to Build Effective AI Solutions?

AI Soft Skills

I recently explored the changing requirements of today’s data scientists in a Forbes Technology Council article. While it traditionally has not been the focus, today, soft skills are just as important as technical prowess.

Since AI deals with real-world problems impacting people, communication skills and empathy are the traits that companies want to see in their data scientists.

As I shared in more detail in Forbes, below are a few of the traits that today’s data scientists must have:

  • Communication. The ability to listen and truly hear each stakeholder’s point of view is important in order to understand the business problem, be able to explain the data, and communicate the story behind the data.
  • Empathy. It’s critical to be able to understand and see an issue from another person’s perspective. How does the problem you’re trying to solve impact different people?
  • Collaboration. Software development is a team sport, and the ability to work well with others, cooperate and collaborate is integral to a good outcome.
  • Open-mindedness. Data scientists need to demonstrate not only an openness to viewpoints from people of diverse backgrounds, but they also need to incorporate that diversity into every algorithm they train.
  • A business mindset. Data scientists must operate as part of the business team, using scientific methods to solve real-world business problems.

AI solutions must be trained to think more like humans, and that means they need to become less robotic and more inclusive. That can only happen when the trainers – the data scientists – are more empathetic, understanding and diverse. Train an algorithm with these values, and better, more strategic business decisions will follow.

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