Using H-1B Data for Salary Negotiation
How to use Department of Labor H-1B wage filings on PlainEmployers to benchmark compensation — what the data shows and what it misses.
DOL/ETA's H-1B Labor Condition Applications give every job seeker access to a legally-binding wage floor that the employer already disclosed for the role. Median filed wage at the same employer, in the same metro, for the same SOC code is a hard data point that Glassdoor cannot match — and it travels in your favor at the negotiating table.
Why This Matters
Most candidates anchor compensation discussions to crowdsourced Glassdoor or Levels.fyi numbers — both of which are self-reported, often years out of date, and frequently confused across role levels. H-1B LCAs are different: each filing names the employer, a specific SOC code, a worksite metro, and a prevailing wage tier (Levels 1–4 from BLS OEWS), and the wage floor in the filing is binding under DOL regulation. That's a level of evidentiary strength that recruiters take seriously, especially when paired with multiple recent filings at the same employer.
The challenge is that government data was designed for regulatory compliance and statistical reporting — not for the questions that most people are actually trying to answer. Understanding the gap between what the data measures and what you need to know is essential for drawing valid conclusions from PlainEmployers.
This guide explains how to pull the right LCA filings from PlainEmployers for your role and metro, how to read the prevailing- wage tier so you don't accidentally undershoot, what comparable peer-employer evidence looks like when you're working a counter- offer, and where the data has gaps you should know about before citing it in writing.
Key Concepts to Understand
Prevailing wage and the four-level system: Every LCA filing names a prevailing-wage source (usually OFLC's FLAG portal or the OES Online Wage Library) and a Level 1–4 tier. Level 1 is entry-level (10th percentile of OES wages for the SOC code + metro), Level 4 is fully-competent independent contributor (62.5th percentile). Filed wage must equal or exceed the prevailing wage at that tier. If a recruiter offers you a number near Level 2 for a Level 3-titled role, the LCA-disclosed Level 3 wage for that same employer in the same metro is the lever to lift the offer.
Same-employer, same-metro, same-SOC matching: Median wage across all H-1B filings nationally is not what you want. You want median across filings at the SAME EMPLOYER, in the SAME METRO, for the SAME six-digit SOC code, within the most recent two filing cycles. PlainEmployers' employer detail page groups filings this way so the comparison is apples-to-apples. A national median can hide a 30–40% pay gap between Manhattan and Cleveland for the same role and tier.
What LCAs do NOT capture: LCAs disclose base wage only. Total compensation — equity grants, annual bonus targets, sign-on bonuses, RSU refresh schedules — is not part of the LCA filing and not in the dataset. For roles where equity is a meaningful share of comp (FAANG, late-stage startups), LCA data sets a hard floor for base but does not benchmark the full package. Treat the LCA wage as the salary anchor and negotiate the equity tier separately, using Levels.fyi or 1:1 conversations with peers at the company.
Common Misconceptions
The most common mistake is treating the LCA wage as a market-rate salary number rather than a regulatory floor. Many employers file LCAs at the prevailing-wage minimum and then pay the actual hire materially above that floor. The "filed wage" is a binding floor, not a typical salary. Use the filed wage as a baseline-protection argument ("I know the floor is X, so I expect at least Y on top of that"), not as the final negotiating anchor.
Another common mistake is assuming more recent data is always more relevant. Government data typically has a reporting lag of 12-24 months. The most recent available figures may describe conditions that have already changed, particularly in rapidly evolving sectors or regions. Always note the data vintage when making time-sensitive decisions.
A third misconception is that government data is always complete. In reality, reporting thresholds, voluntary participation rates, and processing delays mean that every dataset has gaps. PlainEmployers presents data as reported by source agencies, noting gaps where they are known. Absence of data does not mean absence of activity.
Practical Steps for Using the Data
Step 1 — Start with the big picture. Before drilling into specific records, check the broad trends on PlainEmployers. What is the overall direction? Is the pattern you are investigating part of a larger trend or an isolated anomaly?
Step 2 — Compare appropriately. When evaluating any specific data point, compare it against similar entities rather than the national average. Geographic, industry, and size differences create natural variation that makes broad comparisons potentially misleading.
Step 3 — Check the source documentation. Every data point on PlainEmployers traces back to a government source. When the stakes are high — career decisions, policy analysis, research publications — verify critical figures against the primary source. We provide source attribution on our data pages and about page.
Step 4 — Apply judgment that data cannot provide. Data is a starting point, not a final answer. The best decisions combine quantitative data with qualitative context — local knowledge, expert consultation, and direct observation. Use PlainEmployers data to narrow your focus and inform your questions, not to replace professional judgment or lived experience.
Frequently Asked Questions
What data does PlainEmployers use?
PlainEmployers uses data from DOL H-1B filings, OSHA safety records, and WARN Act notices. All data comes from public sources and is processed through our pipeline for searchability and analysis.
How often is the data updated?
We update our database as new data becomes available from source agencies. Frequency depends on the source release schedule, which varies from monthly to annually depending on the dataset.
How should I interpret the data?
Always compare within appropriate reference groups. Aggregate statistics describe populations, not individual cases. See our full guide library for detailed interpretation frameworks.
Is PlainEmployers free to use?
Yes. PlainEmployers is completely free, requires no account, and is supported by non-intrusive advertising. We believe public data should be freely accessible to everyone.
Sources: DOL H-1B filings, OSHA safety records, and WARN Act notices.
Last updated: April 2026
Quick reference table
| Signal | Source | Cadence | Use it for |
|---|---|---|---|
| H-1B labor condition application | DOL OFLC | Quarterly | Wage benchmarking + visa-sponsorship history |
| OSHA DART injury rate | OSHA ITA | Annual | Workplace injury benchmark vs industry mean |
| WARN Act notice | State workforce agency | Event-driven | Mass-layoff history + 60-day notice context |
| Composite safety grade | PlainEmployers (derived) | Annual | Quick A-F readout normalized across NAICS sectors |
How to use this guide in practice
Open this guide in one tab and a live employer profile in a second tab. Each section below maps to a section on the profile page, so you can read along while inspecting real data on a specific company you care about.
Worked example: comparing two retail employers
Suppose Employer A files 250 H-1B applications at $95,000 median wage with a Grade B safety record and 0 WARN notices in the last 3 years, while Employer B files 30 H-1B applications at $120,000 median wage with a Grade D safety record and 4 WARN notices affecting 1,200 workers. The $25,000 wage premium at Employer B is a real signal, but the safety and stability gaps point in the opposite direction. A reader applying the framework above would weigh those gaps against personal risk tolerance and career stage before deciding which offer to pursue.
Cross-references inside PlainEmployers
Every guide in this series links to live data pages. Browse all employers, look up an individual state, or compare industry sectors to apply each concept immediately.
External authoritative sources
Every claim in this guide cites a primary federal source — the U.S. Department of Labor Office of Foreign Labor Certification, the Occupational Safety and Health Administration Injury Tracking Application, or state workforce-agency WARN registries. We do not cite secondary aggregators, opinion sites, or paywalled databases.
