The U.S. job market has been on a roller coaster ride in the nearly four-and-a-half years since the Covid pandemic shut down most businesses globally. It mostly has been scorching hot in that time, transferring power to employees in the form of higher salaries, more mobility and more opportunity. But starting nearly two years ago, tech companies bucked that trend and began shedding jobs. According to a tracker established by Crunchbase, public and private tech companies slashed more than 93,000 jobs in 2022. They followed that up in 2023 by cutting more than 190,000. So far this year, tech companies have let at least 77,000 workers go.

And, it isn’t just startups on tight budgets that are feeding these increases. Some of the most valuable companies in the world, including Amazon, Alphabet, Meta and Microsoft—businesses that have been propping up stock prices globally in recent years—each laid off more than 10,000 employees in 2023.

Data jobs of all kinds were clearly included in the tech companies’ cost-cutting moves, but it’s difficult to pinpoint exactly what roles suffered the most and what the prospects are for data professionals moving forward.

Really feeling the pinch?

While some data pros felt—and continue to feel—pain associated with layoffs and the inability to find jobs in a field that was promised to provide significant employment opportunities, the great tech purge of the last two years may not have been the bloodbath for data that it was for other parts of the industry.

A 2023 analysis by 365DataScience found that layoffs by tech companies hit HR and talent sourcing hardest, followed by software engineers (27.8 percent and 22.1 percent of those laid off, respectively). Data jobs didn’t even register in the overall results, present only in the 34 percent characterized as “others.”

When 365DataScience looked at some individual companies, a clearer picture emerged. Data scientists accounted for 2.7 percent of Amazon’s laid off personnel. Former Meta data analyst and data scientists accounted for 4.3 percent of that company’s layoffs. And 6.3 percent of Microsoft’s layoffs affected cloud and data centers.

Data analytics YouTuber Thu Vu backed that notion up with an analysis of her own that found, since November 2022, despite several points over the past few years where tech layoffs significantly increased, the number of job postings for data scientists, engineers an analysts dipped only 15 percent and didn’t see huge reductions during or right after the two huge layoff spikes at the beginning of 2023 and 2024.

But that doesn’t mean the number of those positions is growing significantly, especially in light of the fact that the U.S. Bureau of Labor Statistics expects the market for data scientists to grow by nearly a third between 2022 and 2032—significantly faster rate than most other job types.

At the same time, the popularity of data-related college majors—spurred by the emergence of AI and the idea of businesses using ever-increasing amounts of data for decision-making—has exploded. Data from the National Center for Education Statistics found that the number of students completing graduate degrees in the U.S.—and the number of institutions granting them—has surged in recent years. In the first three years the NCES has been tracking that data for Data Science and Data and Data Analytics master’s degrees (2020-2022) the number of degrees conferred in Data Science rose from 160 to 1,208 and Data Analytics jumped from 344 to 1,681. The number of universities offering those graduate degrees increased from 13 to 41 and 15 to 49, respectively.

So, while tech layoffs didn’t affect data-related jobs as much as others, there are more unemployed data professionals with experience trying to find work than ever before. Added to the increasing number of graduates with data majors, there are simply significantly more candidates competing for a limited—and stagnating—number of roles. And, that is all occurring just as the overall job market shows the most weakness it has in three years. The Department of Labor reported recently that the unemployment rate for July rose to 4.3 percent—up from 4.1 percent in July and is at its highest level since September of 2021.

The difficulty  job seekers are feeling—and communicating on social media—is real.

Optimizing the Data Job Search

Hopefully, the predicted surge in the number of positions companies need to fill on their data science, engineering and analytics teams will return. Until then, however, what can someone looking for one of those roles do to differentiate themselves from a throng of others.

Persistence, upskilling and continuing education remain the best way to make yourself a more attractive job candidate. Even if you’ve just finished a degree in data science or analytics, there are additional skills you can learn to enhance your resume.

According to YouTuber Vu, if you don’t know the Python and SQL programming languages, you are already behind your peers, even at the entry level. Just about everyone uses Python. And, while she says some might scoff at SQL as antiquated, it is actually essential for every data analyst’s career.

“Don’t overlook SQL,” she says. “It’s more than just a query language. It’s a way of thinking about data that can make you a better data professional overall.”

Also, as LLMs take over the world, in-depth knowledge of prompt engineering and AI agent workflow engineering can prepare you for newly emerging roles like AI Engineer, giving you a broader set of roles you can serve in to bring value to a business.

Learning new skills requires reading a wide range of industry publications, academic research and expert commentary. Opportunities to bolster your knowledge base exist everywhere. Data Universe produces a wide range of content focused on delivering learning opportunities to data professionals both in person and online. The next opportunity to do that is tomorrow in a virtual event titled Maximize Data & AI Potential. It will take place on Aug. 15 from 11 a.m. to 12 p.m. The event will feature Emili Budell-Rhodes, a director of engineering culture change at LexisNexis, and Veronika Durgin, the vice president of Data for Saks, who will help you explore how to build your own unicorn, because every company has its own unique parameters and needs.