The average data scientist earns nearly $100,000 a year – and barriers to entry for applicants are being removed

  • There is a shortage of experienced data science talent.
  • Companies say they face inflated wages and increased competition to hire.

Companies are facing a shortage of experienced talent data scientists due to changing technology and inflated wages.

The need for data scientists has moved beyond traditional technical roles. The number of jobs requiring data science skills is expected to increase by 27.9% by 2026, according to the US Bureau of Labor Statistics.

Matthew Forshaw, senior skills adviser at the Alan Turning Institute, said his research into data skills in the UK revealed a growing demand for professionals in finance, insurance and of manufacturing.

Rising demand is putting pressure on recruitment across the sector, with companies reporting they are struggling to find experienced candidates.

“It’s a new discipline, it’s changed a lot,” Libby Kinsey, head of data science at Ocado, a UK-based company that licenses grocery technology, told Insider. “So it’s quite difficult to find the right people with the right skills.”

“I would say the shortage is very much for leaders and very experienced people,” said Claire Lebarz, guest data science manager at Airbnb. “And the wage war that we’re seeing isn’t helping at all.”

Data scientists in the United States earn an average base salary of $97,000 per year, according to Payscale. But senior data scientists at the biggest companies can earn more than double that average. Data scientists at Facebook’s parent company Meta, for example, can earn up to $260,000 in base salary per year, according to leaked foreign labor data.

Senior data scientists and industry experts told Insider what they look for in new hires.

Academic backgrounds may vary.

Business leaders told Insider they are moving away from hiring candidates from a traditional, highly academic background.

Rather than recruiting from a small group of applicants with a PhD or computer science degree, many companies are beginning to widen the network to those who are self-educated or from another academic background.

“Initially, I think the team came with PhDs from Stanford and Berkeley,” Airbnb’s Lebarz said. “But we’ve been proactively hiring for different profiles that don’t even need to have a PhD – we don’t think that’s necessary to get into data science, you might have a master’s, a baccalaureate or continuing education.

“As demand has grown, so has supply,” said Kinsey of Ocado. “The barriers to entry are coming down. There are lots and lots of really great free courses and materials available,” she said.

“There’s probably a place for everyone, given the range and variety we do,” she added. “There is obviously a threshold, so you have to be able to do coding and be able to talk about machine learning algorithms”

Candidates need more than just technical skills.

Companies are looking for problem solvers and good communicators as well as technical experts.

“Ten years ago, it was hard to find people who were technically strong enough,” said Airbnb’s Lebarz. “But that’s not the case anymore. I think training has evolved so much and there are so many resources online that people are really technically super.”

Companies are looking for candidates who are not only technically strong enough, but “have product and business acumen,” according to Lebarz. “You try to influence a lot of different people,” she said. “So being a good communicator really makes a huge difference.”

“It’s a lot about problem solving. And we really like people who are driven by the problem and not by the use of any particular technique or tool,” she said.

“It’s less about the core machine learning that most companies are looking for,” Turing’s Forshaw added. “It’s more around the kind of visualization, communication, storytelling.”

Sean N. Ayres