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STEM job security did not disappear, but it was never a guarantee. U.S. data still show lower unemployment, higher earnings and faster projected employment growth for STEM overall than for non-STEM work. Those advantages vary substantially by occupation and industry, so a STEM degree is best viewed as a potential labor-market advantage—not insurance against layoffs or a substitute for keeping skills current.
What the latest numbers say about STEM work
Two federal snapshots point in the same direction, though they measure different things. The National Science Foundation (NSF) reports outcomes for workers in 2024; the U.S. Bureau of Labor Statistics (BLS) reports 2024 median wages and employment projections through 2034. The figures below are national aggregates, not a forecast for any particular worker.
| Measure | STEM | Non-STEM | Source and period |
|---|---|---|---|
| Unemployment rate | 2.4% | 3.5% | NSF, 2026; workers in 2024 |
| Median annual earnings | $80,000 | $60,000 | NSF, 2026; workers in 2024 |
| Median annual wage | $103,580 | $48,000 | BLS, 2025; occupations, 2024 |
| Projected employment growth | 8.1% | 2.7% | BLS, 2025; 2024–34 |
The earnings measures come from separate sources and should not be treated as interchangeable: NSF reports median annual earnings for workers, while BLS reports median wages for occupations. Neither figure tells you what a new graduate will earn; experience, location, occupation and employer all matter.
Why “STEM” does not mean one level of security
STEM spans computing, engineering, life and physical sciences, social sciences and other fields. Demand can differ even among occupations that use similar technical skills. BLS’s 2026 projections show this spread across broad occupational groups:
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| Occupation group or specialty | Projected employment growth, 2024–34 | Source |
|---|---|---|
| Computer and mathematical occupations | 10.1% | BLS, 2026 |
| Architecture and engineering occupations | 5.3% | BLS, 2026 |
| Life, physical and social science occupations | 5.0% | BLS, 2026 |
| Data scientists | 33.5% | BLS, 2026 |
| Information security analysts | 28.5% | BLS, 2026 |
The two specialty figures are projections for U.S. employment over a ten-year period, not promises of openings for every applicant. A fast-growing occupation can still be competitive, and national growth does not guarantee stability at a particular company. Conversely, slower projected growth for a broad group does not mean every job in it is shrinking.
STEM is also a substantial and expanding part of the U.S. workforce: NSF and the National Science Board counted 36 million STEM workers in 2023, or 25% of workers, and reported 26% growth in STEM employment from 2013 to 2023. These historical totals describe the field’s scale; they do not establish that an individual role will remain secure.
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What changed about the old promise
The idea that a technical degree automatically leads to durable employment is too simple. The aggregate advantage remains visible in unemployment, earnings and projections, but the mix of work and required competencies changes. NSF has identified data analytics, artificial intelligence, cybersecurity and environmental sciences as areas shaping the evolving STEM workforce.
That shift makes the useful question less “Is STEM safe?” and more “Which occupation, in which industry, uses skills I can keep relevant and take elsewhere?” A technical role tied to a narrow product, funding source or business cycle can face different risks from a role whose skills transfer across employers and sectors. The official figures here do not provide a comparable national measure of layoffs, job tenure or lifetime security, so they cannot show that STEM workers are protected from job loss.
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For a personal-finance decision, compare a specific occupation and education route rather than relying on the STEM label. BLS growth and wage data are useful inputs, but they do not by themselves establish whether a program’s cost will pay off for a particular student.
- Check the occupation, not just the major. Look at projected employment growth and expected openings for the job you are targeting. Broad categories can hide large differences between specialties.
- Estimate realistic earnings. Use occupation-level wage information as a benchmark, then account for location, experience and the types of employers available to you. A national median is not an entry-level salary offer.
- Compare the full entry cost. Include tuition, fees, time out of paid work and any additional licensing or training required. Weigh those costs against plausible early-career earnings, not the highest salary associated with the field.
- Consider resilience and concentration. Ask whether local opportunities depend heavily on one employer or industry and how exposed that industry may be to economic cycles. The national projections do not answer these questions for a particular region.
- Look for transferable skills. Skills that can be used across employers or sectors may give you more options if one role or industry contracts. Relevant capabilities are evolving in areas including analytics, AI, cybersecurity and environmental science.
- Account for the cost of staying current. Find out whether the field expects ongoing learning and what that means in time and money. Treat continuing education as part of the career’s potential cost, not an automatic guarantee of employment.
NSF and the National Science Board describe science and engineering as central to prosperity and power, and the National Science Board has identified data science, information security analysis and operations research analysis among the fastest-growing S&E occupations projected for 2024–34. That is evidence of national demand, not a personal return-on-investment calculation. The decision still depends on the program’s cost, your likely route into the occupation and your alternatives.
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