The average data scientist earns almost $100,000 a year — and the barriers to entry for candidates are being broken down

Due to technology and inflated salaries, companies are facing a talent shortage.

Data specialists are more in demand than traditional tech roles. According to the US Bureau of Labor Statistics, the number of jobs requiring data science skills will grow by 27.9% over the next six years.

There is a growing need for professionals in the finance, insurance, and manufacturing sectors according to Matthew Forshaw, senior advisor for skills at The Alan Turning Institute.

Companies are struggling to find experienced candidates due to the increased demand.

"It's a new discipline, it's been changing quite a lot," Kinsey said. It is difficult to find people with the right skills.

There is a shortage on the leadership side and very senior people. The salary war isn't helping at all.

The average base salary for data scientists in the US is $97,000. Senior data scientists can make more than double the average. According to foreign labor data, data scientists at Facebook's parent company can make up to $260,000 a year.

Insider spoke to experienced data scientists and industry experts about what they look for in a new hire.

Academic backgrounds can vary.  

According to company leaders, they are moving away from only hiring candidates from a traditional highly academic route.

Instead of 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.

Lebarz thought the team was coming with PhDs from Berkeley. We hired for different profiles that don't need to have PhDs, it may be that you have masters, bachelors, or some continuous education."

Kinsey said that demand and supply have increased. There are fewer barriers to entry. There are a lot of free courses and material to choose from.

She said that there is probably a place for everyone. You need to be able to code and talk about machine learning.

Candidates need more than just technical skills.

Problem-solvers and strong communicators are what companies are looking for.

It used to be difficult to find people that were strong enough. The training has evolved so much that people are better technically.

According to Lebarz, companies are looking for candidates who have product and business sense. Being a strong communicator can make a big difference.

There is a lot of problem-solving involved. She said that they were interested in people that were motivated by the problem and not by using a tool.

The core machine learning that most companies are looking for is not the main focus. It's more about visualization, communication, and telling a story.