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What makes a data scientist in the future?
Some data literacy and critical thinking is the answer.
Exceptional mathematical skills, programming in more than one language are no longer required. Any high-school kid knows enough mathematics to begin their data science journey.
If you are a research scientist, you may have to. But not many data scientists are inventing new algorithms. Instead, they solve practical problems by using them. For them, algorithms are configurable black boxes. Their internals doesn’t matter all the time.
Likewise, you never have to learn programming to become a data scientist. Not anymore. You can use tools such as KNIME, Rapid miner, AutoML, and Data Robot Instead. They allow you to program your logic without a programming language.
Case study: The Royal Bank of Canada sets a great example. Their business people excel at data science, too, with the latest technologies. Here’s a whitepaper that explains their success story.
A lab coat and goggles won’t make a chemist. Likewise, programming skills won’t create data scientists. It’s only a preference.
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