It seems like the “data science” role is quickly disappearing from the job market.
We looked at job posting data over the last 18 months and noticed a 26% drop year over year from October 2021 to October 2022 in the number of data scientist job openings. Similarly, though, the number of data engineers and data analyst job openings rose.
But if you look at data analyst jobs, you’d think the market was hotter than ever. Same with data engineering.
Why is this happening?
The overall data science job market is down 15% year over year when you factor in analysts, ML engineers, and data based product managers. But data scientists are losing ground faster.
But it’s likely because the data science role is getting split into multiple different titles. And conveniently cheaper ones.
A “data scientist” is a luxury while a “data analyst” on the other hand average take home is 30% less. So there’s a shift in companies looking for cheaper labor by changing position tiles to more economical conditions.
We saw this earlier in the year when a recruiting client of Interview Query’s ended up downgrading their data science manager hire from a 200K salary role to just a 120K data analyst IC role.
But this is a silver lining for new graduates in the data analytics field. Now new data analysts can compete for more affordable wages.
And with a few years of experience, they will have more confidence inside of a re-surging labor market.
Looking at machine learning and AI research scientist jobs - we don’t see much in the way of change.
Looking at data science interview data over the past two years - we’re also seeing a slowdown across the board.
Interview data was gathered from our internal interview experience forum and scraped from a variety of websites.
Interview data is usually a smaller sample of the larger market but more representative of actual economic conditions. Many companies will post jobs just make it seem like they’re hiring while actual applications are not being considered or in a hiring freeze.
Big tech companies also suffered the most in this recession and have completely stopped hiring.
Big tech companies also hired a large percentage of the total “data scientist” jobs that existed. Since data science is a premium role, big tech companies were the ones generally spearheading the premium cost.
You can see the clear split starting in April 2022 when the hiring freezes started across Meta and other companies began.
A larger proportion of data scientists, in general, were hired at Big Tech companies (Facebook, Google, Amazon, etc.).
Now that there’s a slowdown in hiring across Big Tech, we’re seeing the data science role affected by the sheer proportion that Big Tech constituted across all data science hiring.
We should see in the next year or so this effect in lower data science salaries.
The data engineering market is still booming. While the rise in analysts could be a shift towards a cheaper data science job market, data engineering qualifications still require technical knowledge similar to software engineers.
So the rise in the position could be more attributed to companies slowly understanding how important data infrastructure is.
Additionally, there is also a factor of as data engineering becomes more popular, companies get better at defining the roles for their positions in HR. What could be traditionally a software engineering or data science role, now is being correctly re-labeled into data engineering.
As more companies define data engineering roles, the number of jobs in the space will comfortably rise. And likewise standardization of data engineering interviews will also get better.
So in general - there’s definitely a recession in the data space across all sectors.
While data analyst jobs look like they’re actually up year over year - it’s actually somewhat of a Simpson’s paradox where salaries for the entirety of all data professionals are going down as more roles move to the lower-paying analyst titles.
RSUs also made up most of tech salaries so that’s also going down.
The good news is like always - data science in general is on the frontier of the newest tech development and I think the overarching market should continue to grow.
Generative AI development is pushing more engineers into space than actual data scientists. And blurring the lines in between.
TLDR: There are still jobs - they’re just not the high-paying ones anymore
All data was scraped from Indeed and internally classified using an internal position classification system. You can see the classification in action on our job board here.
The tricky part about analyzing job data now is the rise in companies and recruitment agencies that try to increase their job application rates by duplicating remote jobs across multiple cities. To get around this we tried to de-duplicate jobs by using position titles and descriptions.