# Salary Benchmarks - US Wages by Job Title, State & City (`pushbuild/salary-benchmarks`) Actor

US salary data for about 830 occupations nationally, in every state and every metro area: employment, mean wage and 10th, 25th, median, 75th and 90th percentile hourly and annual pay, from the official BLS wage survey (May 2025).

- **URL**: https://apify.com/pushbuild/salary-benchmarks.md
- **Developed by:** [Pushbuild Data](https://apify.com/pushbuild) (community)
- **Categories:** Business, Jobs, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.50 / 1,000 records

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Salary Benchmarks - US Wages by Job Title, State & City

Pay ranges for about 830 occupations across the United States, every state and every metro area, from the Bureau of Labor Statistics Occupational Employment and Wage Statistics survey (May 2025 release, covering about 1.1 million employers).

### Inputs

Job titles, keywords or SOC codes; locations (US, states, or metro areas such as Boston or Austin); optional area type, minimum employment and sort order.

### Returns

Area name and type, occupation code and title, employment, jobs per 1,000, location quotient, mean hourly and annual wage, and 10th, 25th, median, 75th and 90th percentile hourly and annual wages.

### Uses

Salary benchmarking and compensation planning, job-offer and pay-equity checks, recruiting and job-post pay ranges, relocation and cost comparisons, workforce and site-selection research. Pay per record.

Wages above the survey's top reporting band are not published by BLS and come back empty.

# Actor input Schema

## `occupations` (type: `array`):

Job titles or keywords (all words must match) or SOC codes such as 15-1252. Leave empty for all occupations.

## `locations` (type: `array`):

US (national), state names or abbreviations, or metro area names such as Boston or Austin. A state abbreviation also matches its metro areas. Leave empty for everywhere.

## `areaTypes` (type: `array`):

Limit to national, state or metro.

## `minEmployment` (type: `integer`):

Skip occupations with fewer jobs than this in the area.

## `sortBy` (type: `string`):

Order of results, highest first.

## `maxItems` (type: `integer`):

Maximum records to return.

## Actor input object example

```json
{
  "occupations": [
    "software developers",
    "registered nurses"
  ],
  "locations": [
    "US",
    "MA",
    "Austin"
  ],
  "sortBy": "annualMedian",
  "maxItems": 500
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "occupations": [
        "software developers",
        "registered nurses"
    ],
    "locations": [
        "US",
        "MA",
        "Austin"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("pushbuild/salary-benchmarks").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "occupations": [
        "software developers",
        "registered nurses",
    ],
    "locations": [
        "US",
        "MA",
        "Austin",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("pushbuild/salary-benchmarks").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "occupations": [
    "software developers",
    "registered nurses"
  ],
  "locations": [
    "US",
    "MA",
    "Austin"
  ]
}' |
apify call pushbuild/salary-benchmarks --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,pushbuild/salary-benchmarks"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/HFXtkBoaZcmoTBSBo/builds/nRpTiuFrAdixGUxY4/openapi.json