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Eric Miller, senior director of technical strategy at Rackspace argues, AutoML is poised to turn developers into data scientists — and vice versa. Here’s how AutoML will radically change data science for the better.
Today’s data science roles won’t exist in 10 years
Photo: Getty Images
In the coming decade, the data scientist role as we know it will look very different than it does today. But don’t worry, no one is predicting lost jobs, just changed jobs.
Data scientists will be fine — according to the Bureau of Labor Statistics, the role is still projected to grow at a higher than average clip through 2029. But advancements in technology will be the impetus for a huge shift in a data scientist’s responsibilities and in the way businesses approach analytics as a whole. And AutoML tools, which help automate the machine learning pipeline from raw data to a usable model, will lead this revolution.
In 10 years, data scientists will have entirely different sets of skills and tools, but their function will remain the same: to serve as confident and competent technology guides that can make sense of complex data to solve business problems...
In order to explore the possibilities these types of tools unlock for both developers and data scientists, we first have to understand the current state of data science as it relates to machine learning development. It’s easiest to understand when placed on a maturity scale.
Source: InfoWorld
