Understanding Salary Percentiles: What P10, P50, P90 Mean
Written by Sarah Chen, MS Statistics
Data Analyst | Former BLS Statistical Researcher
Last updated: February 2026 | 10 min read
When researching salaries, you'll frequently encounter terms like "P10," "P50," "median," and "90th percentile." Understanding what these numbers actually mean—and how to use them in your career planning—can be the difference between accepting an underpaying offer and negotiating the compensation you deserve. This guide breaks down salary percentiles in plain English with practical examples.
What Are Salary Percentiles?
A percentile tells you where a specific salary falls within the overall distribution of salaries for an occupation. If a salary is at the 75th percentile, it means that 75% of workers in that occupation earn less than that amount, while 25% earn more.
The Bureau of Labor Statistics (BLS) reports salary data at five key percentiles: 10th, 25th, 50th (median), 75th, and 90th. Together, these give you a complete picture of the salary landscape for any occupation.
The Five Key Percentiles
Breaking Down Each Percentile
P10 (10th Percentile): Entry-Level Baseline
10% of workers earn less than this amount
The P10 represents the lower end of the salary scale. Only the bottom 10% of workers in the occupation earn less than this figure. This typically represents:
- - True entry-level positions with minimal experience
- - Part-time or reduced-hour positions (if included in data)
- - Lower-paying industries within the occupation
- - Smaller companies or lower-cost geographic markets
- - Roles during probationary or training periods
When to expect P10: You're new to the field, changing careers, or entering a small market with limited opportunities.
P25 (25th Percentile): Early Career
25% of workers earn less than this amount
The P25 marks the boundary of the lower quartile. This typically represents:
- - Early career professionals with 1-3 years of experience
- - Competent performers still building their skill set
- - Solid candidates in average-paying industries
- - Workers in medium-sized markets
When to expect P25: You have 1-3 years of experience, are a recent graduate with relevant internships, or work in a moderately competitive market.
P50 (50th Percentile): The Median
50% of workers earn less, 50% earn more
The median is the most important benchmark. It represents the "middle" salary—what a typical, experienced professional earns. This typically represents:
- - Mid-career professionals with 3-7 years of experience
- - Solid performers with proven track records
- - The "market rate" for competent professionals
- - A realistic target for most job seekers with relevant experience
Why median matters: Unlike the average, the median isn't skewed by a few extremely high or low salaries. It's the most accurate representation of what you can realistically expect.
P75 (75th Percentile): Experienced Professionals
75% of workers earn less than this amount
The P75 represents above-average compensation. Only the top 25% of earners make this much or more. This typically represents:
- - Senior professionals with 7-12+ years of experience
- - Those with specialized skills or certifications
- - High performers in demanding roles
- - Workers in high-paying industries (tech, finance, pharma)
- - Employees in major metropolitan areas (NYC, SF, LA)
When to expect P75: You have significant experience, specialized expertise, strong negotiating position, or work in a high-paying market/industry.
P90 (90th Percentile): Top Earners
Only 10% of workers earn this amount or more
The P90 represents the top tier of earners in an occupation. This typically represents:
- - Senior-level or executive positions
- - 12+ years of progressive experience
- - Rare, highly-demanded specializations
- - Leadership roles with team or P&L responsibility
- - Top-paying companies (FAANG, major banks, Big Pharma)
- - Highest cost-of-living markets
Reality check: P90 is aspirational for most workers. Reaching this level typically requires exceptional skills, experience, industry choice, and often some career luck.
Real-World Example: Software Developer Salaries
Let's look at actual BLS data for Software Developers to see percentiles in action:
Software Developer Salary Distribution (U.S. National, 2024)
| Percentile | Annual Salary | Hourly Rate | Typical Profile |
|---|---|---|---|
| P10 (10th) | $74,500 | $35.82 | Junior developer, bootcamp grad, small company |
| P25 (25th) | $95,200 | $45.77 | 1-3 years experience, mid-size company |
| P50 (Median) | $127,260 | $61.18 | Mid-level, 4-7 years, solid performer |
| P75 (75th) | $161,870 | $77.82 | Senior dev, 8+ years, tech hub or big company |
| P90 (90th) | $198,420 | $95.39 | Staff/Principal engineer, FAANG, 10+ years |
Source: Bureau of Labor Statistics, Occupational Employment and Wage Statistics. Note: These are base salaries and may not include bonuses, equity, or other compensation.
This shows the $124,000+ range from P10 to P90. A bootcamp graduate might start at $75,000 while a senior engineer at Google could earn $200,000+ in base salary alone (with total compensation significantly higher).
Median vs. Average: Why the Difference Matters
You might wonder why we focus on median (P50) rather than average salary. The difference is critical for accurate salary research.
Understanding the Difference
Median (P50)
The middle value when all salaries are sorted.
- + Not affected by extreme values
- + Better represents "typical" salary
- + More useful for most workers
- + Preferred by economists and BLS
Average (Mean)
Total of all salaries divided by number of workers.
- - Skewed by very high earners
- - Can be misleadingly high
- - Less representative for most
- - Often reported by recruiters
Example: How Outliers Skew the Average
Imagine a small tech company with 10 employees:
- - 8 developers earning $80,000 each
- - 1 senior developer earning $120,000
- - 1 CTO earning $500,000
Median: $80,000
Accurately represents what most employees earn
Average: $126,000
Inflated by the CTO's salary—no regular developer earns this
If you used the average for salary negotiation, you'd be targeting $126,000 when the realistic market rate is $80,000. This is why median is more useful.
How to Use Percentiles in Salary Negotiations
Understanding percentiles gives you powerful ammunition for salary discussions. Here's how to apply this knowledge:
Step 1: Assess Your Experience Level
Step 2: Adjust for Market Factors
Your target percentile should also account for:
- +High-cost location: Target higher percentile if in SF, NYC, Seattle, Boston
- +High-paying industry: Tech, finance, pharma typically pay above national medians
- +In-demand skills: AI/ML, cloud, cybersecurity command premiums
- +Relevant certifications: CPA, PMP, AWS, etc. can push you up a tier
- -Career change: May need to accept lower percentile initially
- -Smaller market: Rural or smaller metros typically pay less
- -Non-profit sector: Often below market rate for comparable roles
Step 3: Set Your Negotiation Range
Building Your Range Based on Percentiles
Floor (Walk-Away)
Your minimum acceptable: typically P25 for your situation, or one percentile band below your target.
Target (Your Goal)
Based on your experience and market factors: P50 for mid-career, P75 for senior.
Reach (Aspirational)
One percentile band above your target—the high end of what's achievable.
Example: A mid-career professional might set: Floor at P25 ($95,200), Target at P50 ($127,260), Reach at P75 ($161,870).
Finding Your Current Salary Percentile
Wondering where your current salary falls? Here's how to estimate your percentile:
Quick Percentile Estimation
- 1.Find your occupation's salary data on our salary database or BLS website
- 2.Compare your salary to the five percentiles (P10, P25, P50, P75, P90)
- 3.Identify which two percentiles your salary falls between
- 4.Interpolate to estimate your position
Example Calculation:
Your salary: $110,000 | P25: $95,200 | P50: $127,260
Position = (Your Salary - Lower P) / (Higher P - Lower P) * 25 + Lower Percentile
Position = ($110,000 - $95,200) / ($127,260 - $95,200) * 25 + 25
Position = 0.462 * 25 + 25 = 36.5th percentile
Percentile Differences by Location
The same percentile can mean very different dollar amounts depending on location. Here's how Software Developer salaries vary:
Software Developer Median (P50) by Metro Area
| Metro Area | P50 (Median) | vs. National |
|---|---|---|
| San Jose, CA | $167,420 | +32% |
| San Francisco, CA | $161,550 | +27% |
| Seattle, WA | $154,800 | +22% |
| New York, NY | $142,080 | +12% |
| National Median | $127,260 | - |
| Dallas, TX | $118,340 | -7% |
| Atlanta, GA | $112,750 | -11% |
| Phoenix, AZ | $105,200 | -17% |
A developer earning the median in Phoenix ($105,200) would need to earn $167,420 in San Jose to be at the same percentile—a 59% difference. Learn more in our Remote Work Salary Adjustments guide.
Key Takeaways
- P50 (median) is your best benchmark. It represents what a typical professional earns and isn't skewed by outliers like averages.
- P10 represents entry-level. Expect P10-P25 if you're new to a field, changing careers, or in a smaller market.
- P90 is aspirational. Only 10% of workers reach this level, typically after 10+ years and with exceptional skills or roles.
- Location matters enormously. The same percentile can mean 30-50% different dollar amounts across cities.
- Use percentiles to set negotiation ranges. Know your floor (one band below target) and reach (one band above).
Explore Salary Percentiles for Your Occupation
Browse our salary database to see P10, P25, P50, P75, and P90 data for hundreds of occupations across all U.S. metro areas.
Data Sources & Methodology
Percentile data and examples in this guide come from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) survey. The OEWS surveys approximately 1.1 million establishments annually to produce employment and wage estimates for over 800 occupations across all 50 states and metropolitan areas. Percentile calculations follow standard statistical methodology.
About the Author
Sarah Chen, MS Statistics is a data analyst specializing in labor market statistics. She previously worked as a statistical researcher at the Bureau of Labor Statistics, where she contributed to the Occupational Employment and Wage Statistics program. Sarah holds a Master's degree in Statistics from the University of Michigan and is passionate about making complex data accessible to job seekers and career planners.