Increased demand is putting a recruiting squeeze on the entire sector.

There’s a shortage of experienced talent specializing in data science.
Companies say they are facing inflated salaries and increased competition to hire. 
Insider asked experienced data scientists and industry experts what they look for in candidates.

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

The need for data specialists has moved beyond the traditional tech roles. The number of jobs requiring data science skills is projected to grow by 27.9% by 2026, according to the US Bureau of Labor Statistics.

Matthew Forshaw, senior advisor for skills at The Alan Turning Institute, said his research into data skills in the UK found there was a growing demand for professionals in the finance, insurance, and manufacturing sectors.

The increased demand is putting a recruiting squeeze on the entire sector, with companies reporting they are struggling to find experienced candidates.

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

“I would say the shortage is a lot on the leadership side and very senior people,” Claire Lebarz, head of guest data science at Airbnb, said. “And the salary war we’re seeing doesn’t help at all.”

Data scientists in the US make an average base salary of $97,000 a year, according to Payscale. But senior data scientists at top companies can make more than double this average. Data scientists at Facebook’s parent company, Meta, for example, can make up to $260,000 in base salary a year, according to disclosed foreign labor data.

Experienced data scientists and industry experts told Insider what they are looking for in new recruits.

Academic backgrounds can vary.  

Company leaders told Insider they were moving away from only hiring candidates from a traditional highly academic route. 

Rather than recruiting from a small group of candidates with PhDs or computer science degrees, many companies are starting to widen the net to those that are self-trained or from a different academic background.

“Initially, I think the team was coming with PhDs from Stanford and Berkeley,” Airbnb’s Lebarz said. “But we proactively hired for different profiles that don’t even need to have PhDs — we don’t think that’s necessary to go into data science, it may be that you have masters, bachelors, or some continuous education.”

“As demand has increased, so has supply,” Ocado’s Kinsey said. “The barriers to entry are going down. There’s lots and lots of really great free courses and material available,” she said.

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

Candidates need more than just technical skills.

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

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

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

“It’s a lot about problem-solving. And we’re very keen on people that are motivated by the problem and not by using a 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 sort of visualization, communication, storytelling piece.”

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