A tax‑derived salary database covering nearly 25,000 undergraduate programs across the United States turns vague “career prospects” into searchable, comparable hard data.

Many families planning undergraduate studies in the United States run the numbers in their heads: are millions‑worth of tuition and living expenses really worth it?

Should they aim for an Ivy League school or a large public university? Chase rankings or prioritize career outcomes? Are computer science and EE no‑brainer picks? Are humanities and arts destined for low‑paying careers? In the past, such judgments largely drew on anecdotes from parent groups, agency case studies, and unreliable “graduate destination” reports of questionable authenticity.

Now, a tax‑record‑based salary database covering nearly 25,000 undergraduate programs nationwide turns vague “career prospects” into searchable, comparable hard data. Launched by *The New York Times* in partnership with education‑research firm The HEA Group, the dataset draws from U.S. tax records to uniformly report median earnings four years after undergraduate graduation, broken down for every institution and every major.

01 Prestige Cannot Outweigh the Dividends of Your Major Track

Many people take it for granted: getting into a top‑tier school locks in a floor for future earnings.

This dataset suggests otherwise. Four years after graduation, earning potential is often shaped far more by your field of study than by your school’s brand name.

Converted into Renminbi, graduates from a handful of top programs earn close to 2 million RMB four years post‑graduation. By contrast, median earnings for education, humanities, arts and some social‑science programs sit at just above 120 000 RMB — more than a ten‑fold gap.

What is even more striking: median salaries for Ivy‑League majors such as classical literature, history and linguistics frequently lag behind computer‑science and electrical‑engineering programs at state public universities. A prestigious diploma adds value, yet it cannot erase the income divide between different career tracks.

The numbers speak for themselves when looking at subject breakdowns. Among the 20 programs with median annual earnings exceeding $200 000, computer science accounts for 12 spots. Electrical and communications engineering, plus computer and information science each claim two. Computer engineering, mathematics, statistics, and finance and financial management each take one. High‑earning tracks are heavily concentrated and overwhelmingly dominated by STEM fields.

02 The Biggest Pitfall of High‑Earnings Data: Small Sample Sizes

When reviewing these rankings, the most common trap is fixating on eye‑catching figures while ignoring sample size.

Many widely circulated “ceiling‑level salaries” come from niche programs with graduating cohorts of only a dozen‑odd students.

A well‑known example is a mathematics track at Duke University with a sample size of merely 17 graduates. If just two or three students land offers at leading tech firms or hedge funds, the median salary for the whole major gets skewed sharply upward. This figure reflects outcomes for top performers, not realistic expectations for an average admitted student.

The accompanying HEA Group report explicitly warns: salary figures for programs with fewer than 50 respondents should be treated as curiosities rather than grounds for major‑selection decisions. Always examine two metrics together: median earnings and graduate‑sample volume. High earnings observed within large cohorts represent realistic baselines for ordinary students.

03 57 % of International Students Cluster in STEM: Wide Disparities Within Popular Tracks

Key figures come from IIE’s *Open Doors Report 2025*: 57 % of international students heading to the United States enrol in STEM disciplines.

The logic behind this trend is clear: higher earning ceilings, longer OPT work‑authorization periods, and greater availability of domestic roles. Many families overlook, however, that STEM is a broad umbrella category with enormous internal wage gaps.

Computer science, electrical engineering, operations research and statistics sit firmly in the high‑pay tier. Mechanical, civil and chemical engineering fall in the middle bracket. Biology, environmental science and fundamental hard sciences, while qualifying as STEM and granting OPT eligibility, consistently deliver comparatively low salaries. For several such programs, four‑year post‑graduation earnings trail those of many business majors.

The claim “STEM guarantees good jobs” is an oversimplification. More precisely: sub‑fields within STEM such as computer science, electrical engineering, operations research and statistics offer stronger career‑return profiles.

As large numbers of international students flood these sought‑after tracks, competition intensifies: internship requirements grow stricter, new‑grad openings shrink, and the H‑1B lottery becomes more cut‑throat.

Choosing the right field does not guarantee job offers.

04 Four‑Year Salary Figures Are Only a Snapshot

It is critical to emphasise: this dataset only tracks earnings four‑years post‑graduation. It captures short‑term income and does not reflect lifetime‑long earnings.

Findings from Federal Reserve research offer useful context. Five years after graduation, engineering graduates earn an average of nearly $100 000 per year, versus roughly $38 000 for humanities majors — a dramatic gap.

Over a ten‑plus‑year horizon, the pattern shifts. Law, clinical medicine, advanced education and public‑policy roles start with modest pay but deliver substantial mid‑career rewards. By comparison, computer‑science and engineering graduates begin on high salaries yet face persistent pressure from industry cycles, technological disruption and mid‑career competition.

Starting salary and lifetime earnings belong to entirely separate evaluation frameworks.

If a student is passionate about humanities and social sciences and prepared for long‑term dedication, low starting pay does not equal dead‑end prospects. Conversely, forcing yourself into CS purely for high compensation without genuine interest or solid quantitative foundations can lead to heavy course‑load struggles, slipping GPAs and ultimately poorer job outcomes.

05 Three Practical Guidelines for Study‑Abroad Families

These data are not meant to push everyone into computer science, nor to dismiss the value of humanities. Instead, they provide clearer benchmarks for decision‑making.

First, distinguish field‑specific advantages from institutional prestige. Evaluate the long‑term career fundamentals of a major before picking universities — do not reverse this order.

Second, when encountering extraordinary salary numbers, always check sample size. Treat earnings from niche programs with under 50 respondents with caution.

Third, balance return‑on‑investment expectations against personal fit. High‑paying majors generally carry heavier academic pressure and higher attrition rates. Interest, aptitude and resilience matter as much as raw salary statistics.

Studying overseas is a long‑term life choice, not a capital‑guaranteed financial product.

The greatest value of this 25 000‑program salary dataset is not pinpointing “the most profitable major”. It strips away informational bias and lays out expected gains, risks and competitive intensity.

Salary is merely one among many reference points. The optimal choice is a field that aligns with your abilities, rewards sustained effort, and fits your long‑term life‑planning goals.

Note: The New York Times interactive tool lets users search by university and major to view salary outputs alongside sample sizes. Statistics draw from U.S.‑based tax and employment records. If you intend to return to China for work, wage levels and career dynamics differ materially and these figures cannot be directly applied.

If you are navigating U.S. undergraduate admissions, debating major options, or want to understand OPT eligibility, job‑hunting pathways and new‑grad role differences across disciplines, feel free to reach out. Drawing from this salary database, we help build customised plans balancing personal interest and career‑related returns.