Machine learning is spreading from big corporations to smaller companies, and many of its practitioners are relatively new to the technology.

What’s new: Almost one in five data scientists active on Kaggle, which hosts machine learning competitions, have been in the field less than one year, according to the company’s latest State of Data Science and Machine Learning survey. The report covers demographics and employment as well as popular platforms, frameworks, applications, and techniques. The data includes answers from 200,000 people.

What they found: The report tallies responses by 2,675 Kaggle users who identified themselves as employed data scientists.

  • A majority of the respondents had less than three years of machine learning experience, and 18 percent had been in the field less than one year.
  • 37 percent worked at businesses with fewer than 50 employees, a 7 percent rise over last year’s survey. 51 percent worked on teams of fewer than five people.
  • 81.9 percent of respondents identifed as male.
  • Most respondents were in India, making up 21.8 percent of the total. 14.5 percent were in the U.S., and 4.6 percent in Brazil.
  • The U.S. is by far the most lucrative place to be a data scientist, as 73 percent of U.S. respondents said they made over $100,000. In India, the median salary range was between $7,500 and $10,000.

Behind the news: Users of the employment site Glassdoor consistently rank data scientist as one of America’s best jobs, citing good pay and working conditions. But just because workers are happy doesn’t mean they’re sitting still. About a third of the engineers who responded to Anaconda’s 2020 State of Data Science survey said they plan to look for a new job in the coming year. The expected turnover is highest in IT, where 44 percent of data scientists either are actively looking for new employment or plan to do so soon.

Why it matters: This survey underlines how data science is diffusing, not only among businesses but among nations. It highlights trends that hiring managers, among others, should bear in mind, including the field’s ongoing gender imbalance.

We’re thinking: All those newcomers to data science represent a huge pool of fresh ideas and new talent coming in to the field.

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