"Average salary after a master's degree in the USA" is one of the least useful numbers in study-abroad planning, because it blends graduates earning six figures in their first year with graduates earning half that — often from the same university, in the same graduating class, just different departments. The honest answer to "what will I earn" starts with "what field, and is it STEM-designated," not with a single average.
Why "Average" Breaks Down Almost Immediately
A US university-wide average master's salary figure mixes together, for example, a computer science graduate moving into a software engineering role, a public health graduate moving into a nonprofit program-coordinator role, and an English literature graduate moving into a publishing assistant role. These are not variations on a theme — they are different labor markets with different starting points, different growth trajectories, and different degrees of dependence on the master's credential itself.
Before you use any salary figure to plan your finances, ask: is this number specific to my field, or is it a university-wide blend? If it's not field-specific, discount it heavily.
By Field: The Real Driver of Variance
| Field Category | General Pattern | Why |
|---|---|---|
| Computer science / software engineering | Typically the highest starting salaries among master's fields, often entering directly into well-compensated tech roles | High employer demand, STEM-OPT eligibility, strong pipeline from university career fairs to industry |
| Engineering (other disciplines: EE, ME, ChemE, etc.) | Strong salaries, generally below CS but well above the humanities/social science range | STEM-designated in most cases; solid industry demand, though less universally high-paying than software roles |
| Data science / analytics / statistics | Strong salaries, often comparable to or approaching CS-level outcomes | High demand, quantitative skill set transfers across industries, usually STEM-designated |
| Business (non-MBA master's — e.g., MS Finance, MS Business Analytics) | Wide range depending on specialization; quantitative/finance-adjacent tracks tend to pay noticeably more than general business tracks | Some programs are STEM-designated (especially analytics-heavy ones), others are not |
| Life sciences / public health | Moderate and highly role-dependent — research and industry roles pay more than nonprofit/public-sector roles | Mixed STEM status; often requires further credentialing (PhD, licensure) for the highest-paying tracks |
| Humanities / social sciences (history, literature, sociology, political science, etc.) | Typically the lowest starting salaries among master's fields, and the most variable | Rarely STEM-designated; career paths often don't hinge on the specific credential the way technical fields do |
Within every one of these categories, individual outcomes vary hugely by specific role, employer, and location — these are patterns, not guarantees.
STEM-OPT: The Factor That Quietly Reshapes the Whole Picture
For international students specifically, whether your program is STEM-designated (determined by its official CIP code, not by how technical the subject sounds) has an outsized effect on career trajectory that goes beyond the first paycheck:
- Standard OPT gives international graduates 12 months of US work authorization after graduation.
- STEM-OPT extends that by an additional 24 months (36 months total) for graduates of STEM-designated programs, provided the employer is enrolled in E-Verify.
- That extra time matters enormously for the H-1B visa lottery: since selection is random and most years the lottery is oversubscribed, STEM-OPT gives you multiple additional lottery attempts before your work authorization runs out, compared to a single attempt for a non-STEM graduate on standard OPT.
- Employers know this. A candidate with a 3-year work-authorization runway is a materially lower-risk hire than one with 12 months and a single lottery shot — which affects not just whether you get hired, but how seriously some employers take sponsoring you at all.
Practical implication: two students from the same university, one in a STEM-designated master's and one in a non-STEM master's, can face meaningfully different job markets in the US — not because of ability, but because of work-authorization runway. This is worth weighing during program selection, not just after you've enrolled.
What Drives Variance Within a Field
Even inside a single field, expect real spread based on:
- Location — tech-hub cities and major metro areas generally pay more nominally, though cost of living eats into a meaningful share of that premium
- Employer type — large established companies, startups, and public-sector/nonprofit employers pay very differently for similar roles
- Prior work experience — a master's student with several years of relevant pre-degree experience often commands a higher starting offer than one straight from undergrad
- Economic conditions at graduation — hiring markets tighten and loosen year to year, and a graduating cohort's outcomes can look meaningfully different from the cohort just one or two years before or after
Where to Check Real Numbers
Do not plan your finances around a single number from this article or any other blog post. Check:
- Your specific program's published outcomes report, if the university publishes one (career services offices increasingly break this down by department)
- BLS Occupational Employment and Wage Statistics — the US Bureau of Labor Statistics publishes wage data by occupation and region, updated regularly, and is a reliable baseline for role-specific figures
- Payscale, Levels.fyi (especially for tech roles), and Glassdoor for company- and role-specific data points — cross-reference rather than trust any single source
- LinkedIn Salary and industry-specific compensation surveys relevant to your target field
The single most useful thing you can do with "average salary after a master's in the USA" as a search query is stop searching it, and instead search "average salary for [your specific field/role] in [your target city]." That number will actually mean something. The university-wide blend won't.