WageDex guide

Highest-Paying Careers in America

What BLS data reveals about the occupations that pay the most, and what drives those salaries.

The short answer

Pediatric Surgeons top the list at $559,030 a year, but the highest-paid occupations sit far above the $61,390 median across the 825 BLS occupations with a published wage, and most demand a decade of training to reach.

$559,030
Top occupation (Pediatric Surgeons)
$61,390
Median of 825 occupations with published wages
8 of 10
Top earners are medical specialists

The highest salary is rarely the best career choice on its own. Weigh total compensation, education debt, growth outlook, and geographic flexibility alongside raw pay.

Top 10 Highest-Paying Occupations

Based on the most recent BLS OEWS data, these occupations have the highest median annual wages nationally:

Browse the full careers directory to explore wages for all 800+ occupations.

Top 10 occupations by median annual wage

National median wage, U.S. Bureau of Labor Statistics OEWS

median / yr
Source U.S. Bureau of Labor Statistics, OEWS As of May 2025

How rare is top-10 pay?

The 10th-highest occupation's median vs. the 825 BLS occupations with a published median

$312,400 Top 1% higher than 99% of 825 US occupations

$0–$20,000: 0 US occupations (0%). Below this entry. $20,000–$40,000: 98 US occupations (12%). Below this entry. $40,000–$60,000: 298 US occupations (36%). Below this entry. $60,000–$80,000: 209 US occupations (25%). Below this entry. $80,000–$100,000: 82 US occupations (10%). Below this entry. $100,000–$120,000: 58 US occupations (7%). Below this entry. $120,000–$140,000: 32 US occupations (4%). Below this entry. $140,000–$160,000: 14 US occupations (2%). Below this entry. $160,000–$180,000: 9 US occupations (1%). Below this entry. $180,000–$200,000: 25 US occupations (3%). This entry sits in this band. Top-10 line $0 $200,000 every BLS occupation, bucketed by value

Each bar is a $20K-wide band; taller bars hold more US occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count, share, and where it sits relative to this entry.

Source U.S. Bureau of Labor Statistics, OEWS · May 2025

Why Healthcare Dominates

Medical specialists consistently top salary rankings for several interconnected reasons: extensive educational requirements (10-15 years post-high school), high barriers to entry (medical school admission, licensing, board certification), significant liability exposure requiring malpractice insurance, and persistent demand driven by an aging population.

However, the high salaries come with trade-offs rarely discussed in "highest paying jobs" lists: median medical school debt of $200,000+, years of below-market earnings during residency ($60,000-$75,000 for 3-7 years), high burnout rates, and limited geographic flexibility (many specialties require large population centers).

Eight of the ten highest-paid occupations are medical specialists, yet they carry $200,000+ in school debt and years of sub-$75,000 residency pay before the headline salary ever arrives.

WageDex analysis of BLS OEWS, May 2025

High-Paying Technology Careers

Technology occupations don't always appear in the top 10 by median, but they rank exceptionally well at the 75th and 90th percentiles. Software developers, data scientists, and information security analysts have 90th-percentile salaries that rival medical specialties, without the decade of post-graduate training. The key advantage is faster earnings: a software developer can reach the 75th percentile within 5-7 years, while a physician is still in residency.

Compare technology occupations on WageDex to see the full wage distribution, including state-level and metro-level breakdowns.

The ROI Perspective

A better question than "what pays the most?" is "what pays the most relative to the investment required?" Consider:

  • Time to earning potential: A nurse practitioner earns $120,000+ with a master's degree (6 years post-high school), while a specialist physician may need 13-15 years to reach similar or higher earnings.
  • Education debt: Occupations requiring expensive professional degrees must be evaluated net of student loan payments. A $200K salary with $300K in debt is different from a $120K salary with $30K in debt.
  • Geographic flexibility: Some high-paying occupations (airline pilot, software developer) offer location flexibility. Others (specialist physician, investment banker) concentrate in specific metros.
  • Growth trajectory: Some occupations plateau quickly while others have long runway. Management transitions can unlock higher earnings in any field.

Frequently Asked Questions

What is the highest-paying occupation in America?

Family Medicine Physicians top BLS wage rankings with a median salary of $238,380, followed closely by General Internal Medicine Physicians and Airline Pilots. Several specialist physician and dental occupations, including anesthesiologists, oral surgeons, and orthodontists, are among the highest-earning fields nationally but their BLS wage figures are suppressed in this dataset due to small sample sizes, a routine OEWS confidentiality protection, not an indication of lower pay. These occupations require extensive education (medical/dental school plus residency). Among non-medical occupations, chief executives rank among the highest-paid.

Do highest-paying jobs require advanced degrees?

Most of the top 20 highest-paying occupations require a doctoral or professional degree (MD, JD, DDS, PharmD). However, several high-paying careers require only a bachelor's or even no formal degree: airline pilots, air traffic controllers, elevator installers, power plant operators, and some technology roles. Experience and specialized certifications can substitute for formal education in many fields.

Are the highest-paying jobs growing or declining?

It varies significantly, even within healthcare. Nurse practitioners (projected +40.1%) and physician assistants (+20.4%) are among the fastest-growing high-paying occupations as demand shifts toward advanced-practice providers, while physician roles themselves are projected to grow much more slowly (roughly 2.5-4.2% for most specialties) due to a relatively fixed pipeline of medical residency slots. Technology occupations are also growing rapidly, software developers (+15.8%) and data scientists (+33.5%). Some traditionally high-paying roles in law and finance are growing more slowly as automation changes the work.

Does a higher salary always mean more money in your pocket?

Not necessarily. High salaries come with higher tax brackets, and geographic variation matters enormously. A software developer earning $150,000 in San Francisco may have less disposable income than one earning $100,000 in Austin after accounting for taxes, housing, and cost of living. WageDex helps you compare wages across metros.

What are the highest-paying jobs without a college degree?

Airline pilots (median $226,600), air traffic controllers ($144,580), commercial pilots ($122,670), elevator installers and repairers ($106,580), and power plant operators ($99,670) are among the highest-paying occupations that don't require a four-year degree. They typically require specialized training, certifications, or apprenticeships instead.

Why do wages vary so much within the same occupation?

The spread between 10th and 90th percentile wages reflects differences in experience level, geographic location, industry, employer size, and specialization. A software developer at the 10th percentile might earn $65,000 while one at the 90th percentile earns $200,000+. These differences are driven by years of experience, tech stack demand, company revenue, and metro area cost of living.

The Bureau of Labor Statistics OEWS survey, current as of May 2025, is the source: WageDex tracks 831 occupations across 582 U.S. states and metro areas, comprising 36,367 state-level wage records, according to the same federal survey.

Sources

  • U.S. Bureau of Labor Statistics, OEWS, May 2025
  • BLS, Occupational Outlook Handbook

This content is for informational purposes only and does not constitute financial advice.

Understanding the Data

The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.

It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.

For readers who want to conduct their own research, we recommend going directly to the source whenever possible. the U.S. Bureau of Labor Statistics provides detailed documentation on the OEWS survey's collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.

How We Analyze Data Records

Our pipeline pulls the raw OEWS release, standardizes occupation and area names against a fixed taxonomy so the same job title matches across editions, and computes derived figures (percentile bands, metro-vs-national ratios, year-over-year change) that BLS publishes as separate files but most readers want to see side by side.

The metrics we track for every occupation include median and mean annual wage, employment counts, and percentile wage bands (10th through 90th percentile). These figures let you see not just what an occupation pays nationally, but how that compares across metro areas, states, and neighboring occupations, since a single national average can hide wide regional and role-level variation.

"The strongest decisions come from triangulating multiple data sources against your specific situation, not from chasing the latest headline number."

Data & Sourcing Questions

Where does this data come from?

All figures on this page derive from official federal data, primarily the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics and Employment Projections programs. We cite the underlying agency and series in the methodology section. No proprietary aggregators are used.

How often are figures updated?

BLS publishes the OEWS wage release each spring (our data reflects the May 2025 release) and Employment Projections every two years. We refresh our database within 30 days of each upstream release; the methodology page documents the cadence per data series.

Can I use this data for my own analysis?

Yes. The underlying federal data is public domain. Our presentation, calculations, and editorial commentary are licensed for individual reference. For commercial republication or large-scale data extraction, contact us at the email listed on the contact page.

What if the figures here disagree with another source?

Different sources use different methodologies, definitions, geographic boundaries, and reference periods, so disagreement is normal and informative. Our methodology page documents exactly which series and reference period we use for each metric, so you can reproduce or audit the figures against the upstream agency directly.

After reading this guide

A national median is a starting point, here's how to make it personal.

Highest-paying does not mean easiest to enter, many top-paying occupations require years of specialized education or licensure.

Every figure on WageDex is rendered directly from U.S. Bureau of Labor Statistics wage data, no number is typed in by an editor. This guide draws directly on BLS wage data. See our editorial standards & corrections policy, the methodology behind these numbers, or report a data error.