# π° LinkedIn Salary Scraper β Job Pay Ranges & Compensation (`blackfalcondata/linkedin-salary-scraper`) Actor
π° $0.27 per 1,000 results β
Scrape linkedin.com job salaries & pay ranges without login or cookies β compensation, seniority, skills and full employer data. π― Built for salary benchmarking and pay-transparency research.
- **URL**: https://apify.com/blackfalcondata/linkedin-salary-scraper.md
- **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community)
- **Categories:** Jobs, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.27 / 1,000 results
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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
Actors are written with capital "A".
## 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.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
### What does LinkedIn Salary Scraper do?
LinkedIn Salary Scraper extracts pay ranges and compensation from [linkedin.com](https://linkedin.com) job postings β salary min/max, currency, and period, plus seniority, skills, full descriptions, and employer details β with no login or cookies, at $0.27 per 1,000 results. Salary is read from each posting's detail page, which is enabled by default. Coverage is highest on US roles, where pay-transparency laws require a posted range (~70% of US postings carry one).
**New to Apify?** [Sign up free](https://console.apify.com/sign-up?fpr=1h3gvi&fp_sid=ctaplain) and use the included $5 monthly platform credit to test this actor.
### Key features
- **π° Salary & pay ranges** β extracts `salaryMin`, `salaryMax`, `salaryCurrency`, and `salaryPeriod` from each posting's detail page (detail enrichment is on by default β it's where the salary comes from). Highest fill on US roles thanks to pay-transparency laws; postings without a listed range are still returned with the salary fields null.
- **π― Structured filters β or paste a URL** β no URL-building required: set keywords, location, and dropdown filters (date, work type, experience, job type, salary, Easy Apply). Or paste a LinkedIn search URL to reuse its filters β or a single job URL (`.../jobs/view/123β¦`) to pull one posting directly.
- **π’ Company pay ranges** β paste a LinkedIn company-page URL (or numeric companyId) into `companies` and get the compensation for every role that employer is hiring for β no ID lookup needed.
- **π Seniority, skills & role metadata** β each enriched record includes seniority level, employment type, job function, industry, applicant count, and extracted skills alongside the pay range.
- **π Multi-region with presets** β pass `regions: ["US", "GB", "DE"]` for a custom country mix, or pick presets like `"nordic"`, `"dach"`, `"anglosphere"` (salary fill varies by market β US is richest).
- **β‘ Easy-Apply filter** β `easyApply: true` returns only LinkedIn Easy-Apply postings.
- **π« Recruiter-spam filter** β `removeAgency: true` drops third-party staffing-agency listings, keeping direct-employer pay data.
- **π€ AI-ready output** β deterministic `aiSummary` and `skills` fields give compact context for comp-analytics agents and MCP workflows.
- **π Notifications** β Telegram, Slack, Discord, WhatsApp Cloud API, and generic webhook outputs.
- **π¦ Compact mode** β core-fields-only payloads for piping salary data straight into dashboards, spreadsheets, or LLM context.
### What data can you extract from linkedin.com?
Each result includes Core job fields (`scrapedAt`, `portalUrl`, `jobId`, `linkedinJobId`, `jobUrl`, `title`, `location`, and `country`, and more), extended fields (`description`, `descriptionHtml`, `descriptionMarkdown`, and `postingBenefits`), apply information (`applyUrl`, `applyType`, and `easyApply`), and company metadata (`company`, `companyUrl`, `companyId`, and `companyLogo`). In standard mode, all fields are always present β unavailable data points are returned as `null`, never omitted. In compact mode, only core fields are returned.
### Input
The main inputs are an optional location filter and a result limit. Additional filters and options are available in the input schema.
Key parameters:
- **`keywords`** β Job search keywords (e.g. "software engineer", "nurse"). Leave blank to browse all jobs in the selected location.
- **`location`** β City, state, region, or country (e.g. "Berlin, Germany", "United States"). LinkedIn resolves it for you β no IDs needed. Leave empty for global results.
- **`geoIds`** β Advanced/optional override β most users just use π Location, which LinkedIn resolves automatically. For exact targeting, paste a LinkedIn jobs search URL into π Start URLs (the geoId is read for you), or copy the numeric geoId from a LinkedIn jobs URL. Each geoId becomes a separate query, deduped on jobId. (default: `[]`)
- **`regions`** β Two-letter country codes (e.g. "US", "GB", "DE"). Resolved to LinkedIn country geoIds. Use geoIds[] for unsupported markets. (default: `[]`)
- **`regionPresets`** β Pre-defined country grouping. Combined with regions[] if both are set.
- **`datePosted`** β Filter by posting recency. "lastHour" is unique to this scraper. (default: `"anytime"`)
- **`jobType`** β Multi-select employment type filter. (default: `[]`)
- **`experienceLevel`** β Multi-select seniority filter. (default: `[]`)
- **`workType`** β Multi-select onsite/remote/hybrid filter. (default: `[]`)
- **`salaryMin`** β Minimum annual salary (USD). Mapped to LinkedIn's nearest f_SB2 bucket. Post-filtered exactly.
- **`salaryMax`** β Maximum annual salary. Post-filtered (LinkedIn has no native max filter).
- **`salaryIncludeUnknown`** β When salaryMin/Max set, include jobs with no salary data. (default: `true`)
- ...and 40 more parameters
### Input examples
**Basic search** β Keyword-driven search with a result cap.
β Full payload per result β all standard fields populated where the source provides them.
```json
{
"keywords": "software engineer",
"maxResults": 50
}
````
**Filtered search** β Narrow results with advanced filters β only matching jobs are returned.
β Same field set as basic search; fewer, more relevant rows.
```json
{
"keywords": "software engineer",
"jobType": [
"fulltime"
],
"workType": [
"onsite"
],
"experienceLevel": [
"internship"
],
"maxResults": 100
}
```
**Incremental tracking** β Only emit jobs that changed since the previous run with this `stateKey`.
β First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set `emitUnchanged: true` to include unchanged records as well.
```json
{
"keywords": "software engineer",
"maxResults": 200,
"incrementalMode": true,
"stateKey": "software-engineer-tracker"
}
```
**Compact filtered output** β Combine filters with compact mode for a lightweight AI-agent or MCP data source.
β Core fields only β ideal for piping into LLMs or downstream tools without token overhead.
```json
{
"keywords": "software engineer",
"jobType": [
"fulltime"
],
"workType": [
"onsite"
],
"maxResults": 50,
"compact": true
}
```
### Output
Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.
### Example job record
```json
{
"scrapedAt": "2026-04-27T19:02:37.769Z",
"portalUrl": "https://www.linkedin.com",
"source": "linkedin",
"jobId": "1705fc4ee704bf3584cf2654b20e8f95383167563ff7ecd0184b58d2c7d66236",
"linkedinJobId": "4406118990",
"jobUrl": "https://www.linkedin.com/jobs/view/software-engineer-new-grad-at-notion-4406118990",
"title": "Software Engineer, New Grad",
"company": "Notion",
"companyUrl": "https://www.linkedin.com/company/notionhq",
"companyId": "notionhq",
"location": "San Francisco, CA",
"country": "CA",
"postedAt": "2026-04-24T00:00:00.000Z",
"applyUrl": "https://www.linkedin.com/jobs/view/software-engineer-new-grad-at-notion-4406118990",
"applyType": "unknown",
"description": "About Us Notion helps you build beautiful tools for your lifeβs work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, seamlessly connecting docs,...",
"descriptionHtml": "About Us
Notion helps you build beautiful tools for your lifeβs work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, sea...",
"descriptionMarkdown": "About Us Notion helps you build beautiful tools for your lifeβs work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, seamlessly connecting docs,...",
"seniorityLevel": "Not Applicable",
"employmentType": "Full-time",
"industry": "Software Development",
"jobFunction": "Engineering and Information Technology",
"applicantCount": 200,
"easyApply": false,
"contentHash": "eda6ea0d0ad7711b94b796376d0ace88eaf03a62afdefe9708fa4f1c7ae4ae8f",
"isPromoted": false,
"postingBenefits": [
"Actively Hiring"
],
"trackingId": "U6ZtuvNYKrwizG8bYR1Kqw=="
}
```
### Incremental fields
When incremental mode is on, each record also carries:
- `changeType` β one of `NEW`, `UPDATED`, `UNCHANGED`, `REAPPEARED`, `EXPIRED`. Default output covers `NEW` / `UPDATED` / `REAPPEARED`; set `emitUnchanged: true` or `emitExpired: true` to opt into the others.
- `firstSeenAt`, `lastSeenAt` β ISO-8601 timestamps tracking the listing across runs.
- `isRepost`, `repostOfId`, `repostDetectedAt` β populated when a new listing matches the tracked content of a previously expired one. Set `skipReposts: true` to drop detected reposts from the output.
### How to scrape linkedin.com
1. Go to [LinkedIn Salary Scraper](https://apify.com/blackfalcondata/linkedin-salary-scraper?fpr=1h3gvi) in Apify Console.
2. Configure the input and optional location filter.
3. Set `maxResults` to control how many results you need.
4. Click **Start** and wait for the run to finish.
5. Export the dataset as JSON, CSV, or Excel.
### Use cases
- Benchmark salaries for a role across a market or city.
- Build compensation datasets for HR, comp, and pay-equity analytics.
- Track pay ranges by company, seniority, and location over time.
- Pull every pay range at a specific employer by pasting its company URL.
- Research pay-transparency compliance and prevailing market rates.
- Feed structured salary data into dashboards, warehouses, or AI agents using compact mode.
### How much does it cost to scrape linkedin.com?
LinkedIn Salary Scraper uses [pay-per-event](https://docs.apify.com/platform/actors/paid-actors/pay-per-event) pricing. You pay a small fee when the run starts and then for each result that is actually produced.
- **Run start:** $0.0005 per run
- **Per result:** $0.00027 per job record
Example costs:
- 10 results: **$0.0032**
- 25 results: **$0.00725**
- 100 results: **$0.028**
- 200 results: **$0.054**
- 500 results: **$0.14**
#### Example: recurring monitoring savings
These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of jobs that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency β the scenarios below are examples, not predictions.
Example setup: 250 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.
| Churn rate | Full re-scrape run cost | Incremental run cost | Savings vs full re-scrape | Monthly cost after baseline |
|---|---:|---:|---:|---:|
| 5% β stable niche query | $0.07 | $0.00387 | $0.06 (94%) | $0.12 |
| 15% β moderate broad query | $0.07 | $0.01 | $0.06 (84%) | $0.32 |
| 30% β high-volume aggregator | $0.07 | $0.02 | $0.05 (69%) | $0.62 |
Full re-scrape monthly cost at daily polling: $2.04. First month with incremental costs $0.18 / $0.38 / $0.67 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.
Platform usage is included in the per-result fee shown above.
### FAQ
#### How many results can I get from linkedin.com?
The number of results depends on the search query and available jobs on linkedin.com. Use the `maxResults` parameter to control how many results are returned per run.
#### Does LinkedIn Salary Scraper support recurring monitoring?
Yes. Enable incremental mode to only receive new or changed jobs on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.
#### Can I integrate LinkedIn Salary Scraper with other apps?
Yes. LinkedIn Salary Scraper works with Apify's [integrations](https://apify.com/integrations?fpr=1h3gvi) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.
#### Can I use LinkedIn Salary Scraper with the Apify API?
Yes. You can start runs, manage inputs, and retrieve results programmatically through the [Apify API](https://docs.apify.com/api/v2). Client libraries are available for JavaScript, Python, and other languages.
#### Can I use LinkedIn Salary Scraper through an MCP Server?
Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server?fpr=1h3gvi) that lets AI assistants and agents call this actor directly. Use compact mode, `descriptionMaxLength`, a single `descriptionFormat`, and `excludeEmptyFields` to keep payloads manageable for LLM context windows.
#### Is it legal to scrape linkedin.com?
This actor extracts publicly available data from linkedin.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.
#### Your feedback
If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/linkedin-salary-scraper/issues?fpr=1h3gvi) on the actor's page in Apify Console. Your feedback helps us improve.
### You might also like
- [β‘ LinkedIn Job Scraper β Salary, Company & No Cookies](https://apify.com/blackfalcondata/linkedin-job-scraper?fpr=1h3gvi) β π° $0.27 per 1,000 jobs β
Scrape linkedin.com job postings without login or cookies: salary, skills.
- [Actiris Brussels Job Scraper](https://apify.com/blackfalcondata/actiris-scraper?fpr=1h3gvi) β Scrape all active job listings from actiris.brussels β official Brussels public employment service..
- [AMS Austria Job Scraper β Austrian Public Employment Service](https://apify.com/blackfalcondata/ams-austria-job-scraper?fpr=1h3gvi) β Scrape jobs.ams.at β Austria's official AMS public employment portal, branded "alle jobs" ("all.
- [APEC.fr Scraper - French Executive Jobs](https://apify.com/blackfalcondata/apec-scraper?fpr=1h3gvi) β Scrape apec.fr - French executive job listings with salary ranges, company, location, skills,.
- [Arbeitsagentur Jobs Feed β German Federal Employment Agency](https://apify.com/blackfalcondata/arbeitsagentur-jobs-feed?fpr=1h3gvi) β Scrape arbeitsagentur.de β Germany's official public employment portal with over 1 million live job.
- [Arbetsformedlingen Job Scraper](https://apify.com/blackfalcondata/arbetsformedlingen-scraper?fpr=1h3gvi) β Scrape arbetsformedlingen.se (Platsbanken) β Sweden's official employment portal. Returns 84.
- [Bayt.com Scraper β MENA Jobs with Salary & Skills Filter](https://apify.com/blackfalcondata/bayt-scraper?fpr=1h3gvi) β Scrape bayt.com β the leading Middle East job board spanning UAE, Saudi Arabia, Qatar, Egypt.
- [BestJobs.eu Scraper β Romania job board](https://apify.com/blackfalcondata/bestjobs-eu-scraper?fpr=1h3gvi) β Scrape job listings from BestJobs.eu, a leading Romanian job board. Export salary ranges, remote.
### Getting started with Apify
New to Apify? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=1h3gvi\&fp_sid=ctaplain) β no credit card required.
1. Sign up β $5 platform credit included
2. Open this actor and configure your input
3. Click **Start** β export results as JSON, CSV, or Excel
Need more later? [See Apify pricing](https://apify.com/pricing?fpr=1h3gvi).
# Actor input Schema
## `keywords` (type: `string`):
Job search keywords (e.g. "software engineer", "nurse"). Leave blank to browse all jobs in the selected location.
## `location` (type: `string`):
City, state, region, or country (e.g. "Berlin, Germany", "United States"). LinkedIn resolves it for you β no IDs needed. Leave empty for global results.
## `geoIds` (type: `array`):
Advanced/optional override β most users just use π Location, which LinkedIn resolves automatically. For exact targeting, paste a LinkedIn jobs search URL into π Start URLs (the geoId is read for you), or copy the numeric geoId from a LinkedIn jobs URL. Each geoId becomes a separate query, deduped on jobId.
## `regions` (type: `array`):
Two-letter country codes (e.g. "US", "GB", "DE"). Resolved to LinkedIn country geoIds. Use geoIds\[] for unsupported markets.
## `regionPresets` (type: `string`):
Pre-defined country grouping. Combined with regions\[] if both are set.
## `datePosted` (type: `string`):
Filter by posting recency. "lastHour" is unique to this scraper.
## `jobType` (type: `array`):
Multi-select employment type filter.
## `experienceLevel` (type: `array`):
Multi-select seniority filter.
## `workType` (type: `array`):
Multi-select onsite/remote/hybrid filter.
## `salaryMin` (type: `integer`):
Minimum annual salary (USD). Mapped to LinkedIn's nearest f\_SB2 bucket. Post-filtered exactly.
## `salaryMax` (type: `integer`):
Maximum annual salary. Post-filtered (LinkedIn has no native max filter).
## `salaryIncludeUnknown` (type: `boolean`):
When salaryMin/Max set, include jobs with no salary data.
## `companies` (type: `array`):
Scrape jobs from specific employers. Paste LinkedIn company-page URLs (e.g. https://www.linkedin.com/company/microsoft) or numeric companyIds β URLs are resolved for you, no ID lookup needed. Combine with π Keywords to filter within a company.
## `excludeCompanies` (type: `array`):
Company-name substrings to exclude (case-insensitive post-filter).
## `excludeKeywords` (type: `array`):
Title substrings to exclude (case-insensitive post-filter).
## `easyApply` (type: `boolean`):
Restrict results to LinkedIn Easy Apply postings.
## `removeAgency` (type: `boolean`):
Heuristic post-filter on company name ("recruitment", "staffing", etc.).
## `distance` (type: `integer`):
Search radius around location. LinkedIn auto-detects unit (miles in US/UK/CA/AU/NZ; km elsewhere).
## `sortBy` (type: `string`):
Sort order. "recent" is recommended for incremental feeds.
## `startUrls` (type: `array`):
Paste LinkedIn job URLs from your browser. Two kinds work: a job SEARCH URL (e.g. .../jobs/search?keywords=β¦) reuses all of its filters as the query, or an individual JOB POSTING URL (e.g. .../jobs/view/4012345678) is scraped directly with full detail. Mix both freely.
## `proxyConfiguration` (type: `object`):
Network egress configuration. Use the default unless you need a custom proxy setup.
## `linkedinHost` (type: `string`):
Subdomain (e.g. "www", "de"). Affects default geo-routing + UI labels.
## `outputLanguage` (type: `string`):
HTTP Accept-Language header. Default en-US for parsing-cleanliness.
## `incrementalMode` (type: `boolean`):
Persist seen-jobIds across runs; emit only NEW + UPDATED. Requires stateKey.
## `stateKey` (type: `string`):
Optional stable identifier for the tracked search universe. Leave empty to auto-derive a stable identifier from your search inputs β different keyword/location/filter combinations get isolated state automatically.
## `allowNonIncrementalFallback` (type: `boolean`):
If incremental mode is requested but the state store is not accessible on this account, fall back to a non-incremental run instead of failing. Default: fail loudly so missing state is not silently ignored.
## `outputMode` (type: `string`):
Which items to emit when in incrementalMode.
## `emitUnchanged` (type: `boolean`):
Include items that haven't changed since last run.
## `emitExpired` (type: `boolean`):
Include items that disappeared from search results.
## `skipReposts` (type: `boolean`):
Suppress jobs with the same content as a previously-seen but inactive listing.
## `enrichDetails` (type: `boolean`):
Fetch each job's detail page to extract the salary / pay range plus full description, seniorityLevel, employmentType, jobFunction, industry, and applicantCount. On by default β this is where salary data comes from. Adds 1 HTTP request per job.
## `scrapeCompany` (type: `boolean`):
For each job, fetch the employer's public LinkedIn company page and add company description, website, employee count, logo, and address. Fetched once per unique company.
## `discoverRelated` (type: `boolean`):
After the main search, fetch LinkedIn's related-jobs feed for the first N results to discover roles that don't surface on the keyword search. Useful for thin markets.
## `relatedSeedCount` (type: `integer`):
How many of the first search results are used as seeds for related-jobs expansion. Each seed yields up to 10 candidates.
## `telegramToken` (type: `string`):
Bot token from @BotFather. Leave empty to disable Telegram notifications.
## `telegramChatId` (type: `string`):
Numeric chat or channel ID where notifications should be sent.
## `discordWebhookUrl` (type: `string`):
Channel webhook URL. Leave empty to disable Discord notifications.
## `slackWebhookUrl` (type: `string`):
Incoming webhook URL. Leave empty to disable Slack notifications.
## `whatsappAccessToken` (type: `string`):
Permanent System User token from Meta Business.
## `whatsappPhoneNumberId` (type: `string`):
Numeric phone-number ID from the Meta dashboard.
## `whatsappTo` (type: `string`):
Recipient phone number in E.164 format (e.g. "4561234567").
## `webhookUrl` (type: `string`):
Receives a JSON POST of {metadata, items} for each batch.
## `webhookHeaders` (type: `object`):
Additional HTTP headers to include with the generic webhook (e.g. Authorization).
## `notificationLimit` (type: `integer`):
Cap on items included in each notification message.
## `notifyOnlyChanges` (type: `boolean`):
When in incrementalMode, suppress notifications for UNCHANGED items.
## `compact` (type: `boolean`):
Emit only core fields (keeps cost the same; reduces dataset size).
## `descriptionMaxLength` (type: `integer`):
Truncate description (0 = no truncation). Only relevant when enrichDetails=true.
## `phoneExtractionMode` (type: `string`):
"strict" requires Tel:/+CC prefix; "lenient" also picks up bare local-format numbers.
## `maxResults` (type: `integer`):
Cap on emitted items (0 = unlimited).
## `descriptionFormat` (type: `string`):
Pick a single description representation. `all` keeps every variant; `text` / `html` / `markdown` drop the others.
## `excludeEmptyFields` (type: `boolean`):
Drop null, empty-string, and empty-array fields from each record before push. Smaller, cleaner payloads for AI agents and dashboards. On by default; turn off to always emit every field (including empty ones).
## `appConnector` (type: `string`):
Optional. Pick a connected app under Settings β API & Integrations to receive your results. Notion is supported today (a run-summary page); other MCP connectors are best-effort as Apify expands its catalog.
## `mcpIssueTeam` (type: `string`):
Only when the connected app is an issue tracker: the team (name or ID) the summary issue is created under, if that app requires one.
## Actor input object example
```json
{
"keywords": "software engineer",
"geoIds": [],
"regions": [],
"datePosted": "anytime",
"jobType": [],
"experienceLevel": [],
"workType": [],
"salaryIncludeUnknown": true,
"companies": [],
"excludeCompanies": [],
"excludeKeywords": [],
"easyApply": false,
"removeAgency": false,
"sortBy": "recent",
"startUrls": [],
"proxyConfiguration": {
"useApifyProxy": true
},
"linkedinHost": "www",
"outputLanguage": "en-US,en;q=0.9",
"incrementalMode": false,
"allowNonIncrementalFallback": false,
"outputMode": "all",
"emitUnchanged": false,
"emitExpired": false,
"skipReposts": false,
"enrichDetails": true,
"scrapeCompany": false,
"discoverRelated": false,
"relatedSeedCount": 5,
"notificationLimit": 5,
"notifyOnlyChanges": false,
"compact": false,
"descriptionMaxLength": 0,
"phoneExtractionMode": "strict",
"maxResults": 100,
"descriptionFormat": "all",
"excludeEmptyFields": true
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": "software engineer",
"easyApply": false,
"removeAgency": false,
"incrementalMode": false,
"enrichDetails": true,
"scrapeCompany": false,
"discoverRelated": false,
"compact": false,
"descriptionFormat": "all",
"excludeEmptyFields": true
};
// Run the Actor and wait for it to finish
const run = await client.actor("blackfalcondata/linkedin-salary-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`πΎ 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);
});
// π Want to learn more π? Go to β 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"keywords": "software engineer",
"easyApply": False,
"removeAgency": False,
"incrementalMode": False,
"enrichDetails": True,
"scrapeCompany": False,
"discoverRelated": False,
"compact": False,
"descriptionFormat": "all",
"excludeEmptyFields": True,
}
# Run the Actor and wait for it to finish
run = client.actor("blackfalcondata/linkedin-salary-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("πΎ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# π Want to learn more π? Go to β https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": "software engineer",
"easyApply": false,
"removeAgency": false,
"incrementalMode": false,
"enrichDetails": true,
"scrapeCompany": false,
"discoverRelated": false,
"compact": false,
"descriptionFormat": "all",
"excludeEmptyFields": true
}' |
apify call blackfalcondata/linkedin-salary-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=blackfalcondata/linkedin-salary-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "π° LinkedIn Salary Scraper β Job Pay Ranges & Compensation",
"description": "π° $0.27 per 1,000 results β
Scrape linkedin.com job salaries & pay ranges without login or cookies β compensation, seniority, skills and full employer data. π― Built for salary benchmarking and pay-transparency research.",
"version": "0.1",
"x-build-id": "UBv7DmNQqiGG1aWze"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/blackfalcondata~linkedin-salary-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-blackfalcondata-linkedin-salary-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/blackfalcondata~linkedin-salary-scraper/runs": {
"post": {
"operationId": "runs-sync-blackfalcondata-linkedin-salary-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/blackfalcondata~linkedin-salary-scraper/run-sync": {
"post": {
"operationId": "run-sync-blackfalcondata-linkedin-salary-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"keywords": {
"title": "π Search keywords",
"type": "string",
"description": "Job search keywords (e.g. \"software engineer\", \"nurse\"). Leave blank to browse all jobs in the selected location."
},
"location": {
"title": "π Location",
"type": "string",
"description": "City, state, region, or country (e.g. \"Berlin, Germany\", \"United States\"). LinkedIn resolves it for you β no IDs needed. Leave empty for global results."
},
"geoIds": {
"title": "π LinkedIn geoId (advanced)",
"type": "array",
"description": "Advanced/optional override β most users just use π Location, which LinkedIn resolves automatically. For exact targeting, paste a LinkedIn jobs search URL into π Start URLs (the geoId is read for you), or copy the numeric geoId from a LinkedIn jobs URL. Each geoId becomes a separate query, deduped on jobId.",
"default": [],
"items": {
"type": "string"
}
},
"regions": {
"title": "πΊ ISO-2 region codes",
"type": "array",
"description": "Two-letter country codes (e.g. \"US\", \"GB\", \"DE\"). Resolved to LinkedIn country geoIds. Use geoIds[] for unsupported markets.",
"default": [],
"items": {
"type": "string"
}
},
"regionPresets": {
"title": "π Region preset",
"enum": [
"nordic",
"dach",
"benelux",
"uk-ireland",
"eu-27",
"gcc",
"mena",
"asean",
"anglosphere",
"latam",
"nordics-extended"
],
"type": "string",
"description": "Pre-defined country grouping. Combined with regions[] if both are set."
},
"datePosted": {
"title": "π Date posted",
"enum": [
"anytime",
"lastHour",
"last24h",
"last7d",
"last30d"
],
"type": "string",
"description": "Filter by posting recency. \"lastHour\" is unique to this scraper.",
"default": "anytime"
},
"jobType": {
"title": "πΌ Job type",
"type": "array",
"description": "Multi-select employment type filter.",
"items": {
"type": "string",
"enum": [
"fulltime",
"parttime",
"contract",
"temporary",
"internship",
"volunteer",
"other"
]
},
"default": []
},
"experienceLevel": {
"title": "π Experience level",
"type": "array",
"description": "Multi-select seniority filter.",
"items": {
"type": "string",
"enum": [
"internship",
"entry",
"associate",
"mid_senior",
"director",
"executive"
]
},
"default": []
},
"workType": {
"title": "π Work type",
"type": "array",
"description": "Multi-select onsite/remote/hybrid filter.",
"items": {
"type": "string",
"enum": [
"onsite",
"remote",
"hybrid"
]
},
"default": []
},
"salaryMin": {
"title": "π° Salary min",
"minimum": 0,
"type": "integer",
"description": "Minimum annual salary (USD). Mapped to LinkedIn's nearest f_SB2 bucket. Post-filtered exactly."
},
"salaryMax": {
"title": "π° Salary max",
"minimum": 0,
"type": "integer",
"description": "Maximum annual salary. Post-filtered (LinkedIn has no native max filter)."
},
"salaryIncludeUnknown": {
"title": "Include jobs without salary",
"type": "boolean",
"description": "When salaryMin/Max set, include jobs with no salary data.",
"default": true
},
"companies": {
"title": "π’ Companies β scrape all their jobs (IDs or URLs)",
"type": "array",
"description": "Scrape jobs from specific employers. Paste LinkedIn company-page URLs (e.g. https://www.linkedin.com/company/microsoft) or numeric companyIds β URLs are resolved for you, no ID lookup needed. Combine with π Keywords to filter within a company.",
"default": [],
"items": {
"type": "string"
}
},
"excludeCompanies": {
"title": "π« Exclude companies",
"type": "array",
"description": "Company-name substrings to exclude (case-insensitive post-filter).",
"default": [],
"items": {
"type": "string"
}
},
"excludeKeywords": {
"title": "π« Exclude keywords",
"type": "array",
"description": "Title substrings to exclude (case-insensitive post-filter).",
"default": [],
"items": {
"type": "string"
}
},
"easyApply": {
"title": "β‘ Easy Apply only",
"type": "boolean",
"description": "Restrict results to LinkedIn Easy Apply postings.",
"default": false
},
"removeAgency": {
"title": "π« Remove staffing agencies",
"type": "boolean",
"description": "Heuristic post-filter on company name (\"recruitment\", \"staffing\", etc.).",
"default": false
},
"distance": {
"title": "π Distance (km/mi)",
"minimum": 0,
"type": "integer",
"description": "Search radius around location. LinkedIn auto-detects unit (miles in US/UK/CA/AU/NZ; km elsewhere)."
},
"sortBy": {
"title": "π Sort",
"enum": [
"recent",
"relevant"
],
"type": "string",
"description": "Sort order. \"recent\" is recommended for incremental feeds.",
"default": "recent"
},
"startUrls": {
"title": "π Advanced: start URLs",
"type": "array",
"description": "Paste LinkedIn job URLs from your browser. Two kinds work: a job SEARCH URL (e.g. .../jobs/search?keywords=β¦) reuses all of its filters as the query, or an individual JOB POSTING URL (e.g. .../jobs/view/4012345678) is scraped directly with full detail. Mix both freely.",
"default": [],
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
},
"proxyConfiguration": {
"title": "π‘ Proxy",
"type": "object",
"description": "Network egress configuration. Use the default unless you need a custom proxy setup.",
"default": {
"useApifyProxy": true
}
},
"linkedinHost": {
"title": "π LinkedIn host",
"type": "string",
"description": "Subdomain (e.g. \"www\", \"de\"). Affects default geo-routing + UI labels.",
"default": "www"
},
"outputLanguage": {
"title": "π£ Accept-Language",
"type": "string",
"description": "HTTP Accept-Language header. Default en-US for parsing-cleanliness.",
"default": "en-US,en;q=0.9"
},
"incrementalMode": {
"title": "π Incremental mode",
"type": "boolean",
"description": "Persist seen-jobIds across runs; emit only NEW + UPDATED. Requires stateKey.",
"default": false
},
"stateKey": {
"title": "π State key",
"type": "string",
"description": "Optional stable identifier for the tracked search universe. Leave empty to auto-derive a stable identifier from your search inputs β different keyword/location/filter combinations get isolated state automatically."
},
"allowNonIncrementalFallback": {
"title": "β©οΈ Allow Non-Incremental Fallback",
"type": "boolean",
"description": "If incremental mode is requested but the state store is not accessible on this account, fall back to a non-incremental run instead of failing. Default: fail loudly so missing state is not silently ignored.",
"default": false
},
"outputMode": {
"title": "π€ Output mode",
"enum": [
"all",
"new-only",
"changed-only"
],
"type": "string",
"description": "Which items to emit when in incrementalMode.",
"default": "all"
},
"emitUnchanged": {
"title": "β»οΈ Emit UNCHANGED items",
"type": "boolean",
"description": "Include items that haven't changed since last run.",
"default": false
},
"emitExpired": {
"title": "β°οΈ Emit EXPIRED items",
"type": "boolean",
"description": "Include items that disappeared from search results.",
"default": false
},
"skipReposts": {
"title": "Skip detected reposts",
"type": "boolean",
"description": "Suppress jobs with the same content as a previously-seen but inactive listing.",
"default": false
},
"enrichDetails": {
"title": "π¬ Enrich with detail page (salary source)",
"type": "boolean",
"description": "Fetch each job's detail page to extract the salary / pay range plus full description, seniorityLevel, employmentType, jobFunction, industry, and applicantCount. On by default β this is where salary data comes from. Adds 1 HTTP request per job.",
"default": true
},
"scrapeCompany": {
"title": "π’ Scrape company details",
"type": "boolean",
"description": "For each job, fetch the employer's public LinkedIn company page and add company description, website, employee count, logo, and address. Fetched once per unique company.",
"default": false
},
"discoverRelated": {
"title": "π Expand via relatedJobs",
"type": "boolean",
"description": "After the main search, fetch LinkedIn's related-jobs feed for the first N results to discover roles that don't surface on the keyword search. Useful for thin markets.",
"default": false
},
"relatedSeedCount": {
"title": "relatedJobs seed count",
"minimum": 0,
"maximum": 100,
"type": "integer",
"description": "How many of the first search results are used as seeds for related-jobs expansion. Each seed yields up to 10 candidates.",
"default": 5
},
"telegramToken": {
"title": "Telegram bot token",
"type": "string",
"description": "Bot token from @BotFather. Leave empty to disable Telegram notifications."
},
"telegramChatId": {
"title": "π¬ Telegram chat ID",
"type": "string",
"description": "Numeric chat or channel ID where notifications should be sent."
},
"discordWebhookUrl": {
"title": "Discord webhook URL",
"type": "string",
"description": "Channel webhook URL. Leave empty to disable Discord notifications."
},
"slackWebhookUrl": {
"title": "Slack webhook URL",
"type": "string",
"description": "Incoming webhook URL. Leave empty to disable Slack notifications."
},
"whatsappAccessToken": {
"title": "WhatsApp Cloud API access token",
"type": "string",
"description": "Permanent System User token from Meta Business."
},
"whatsappPhoneNumberId": {
"title": "WhatsApp phone-number ID",
"type": "string",
"description": "Numeric phone-number ID from the Meta dashboard."
},
"whatsappTo": {
"title": "WhatsApp recipient (E.164)",
"type": "string",
"description": "Recipient phone number in E.164 format (e.g. \"4561234567\")."
},
"webhookUrl": {
"title": "Generic webhook URL (n8n / Make / Zapier)",
"type": "string",
"description": "Receives a JSON POST of {metadata, items} for each batch."
},
"webhookHeaders": {
"title": "Webhook headers",
"type": "object",
"description": "Additional HTTP headers to include with the generic webhook (e.g. Authorization)."
},
"notificationLimit": {
"title": "Max items per notification batch",
"minimum": 1,
"maximum": 50,
"type": "integer",
"description": "Cap on items included in each notification message.",
"default": 5
},
"notifyOnlyChanges": {
"title": "Notify only NEW/UPDATED",
"type": "boolean",
"description": "When in incrementalMode, suppress notifications for UNCHANGED items.",
"default": false
},
"compact": {
"title": "Compact output",
"type": "boolean",
"description": "Emit only core fields (keeps cost the same; reduces dataset size).",
"default": false
},
"descriptionMaxLength": {
"title": "Description max length",
"minimum": 0,
"type": "integer",
"description": "Truncate description (0 = no truncation). Only relevant when enrichDetails=true.",
"default": 0
},
"phoneExtractionMode": {
"title": "Phone-extraction mode",
"enum": [
"strict",
"lenient"
],
"type": "string",
"description": "\"strict\" requires Tel:/+CC prefix; \"lenient\" also picks up bare local-format numbers.",
"default": "strict"
},
"maxResults": {
"title": "π― Max results",
"minimum": 0,
"type": "integer",
"description": "Cap on emitted items (0 = unlimited).",
"default": 100
},
"descriptionFormat": {
"title": "Description format",
"enum": [
"all",
"text",
"html",
"markdown"
],
"type": "string",
"description": "Pick a single description representation. `all` keeps every variant; `text` / `html` / `markdown` drop the others.",
"default": "all"
},
"excludeEmptyFields": {
"title": "Exclude empty fields from output",
"type": "boolean",
"description": "Drop null, empty-string, and empty-array fields from each record before push. Smaller, cleaner payloads for AI agents and dashboards. On by default; turn off to always emit every field (including empty ones).",
"default": true
},
"appConnector": {
"title": "Send results to Notion (or another connected app)",
"type": "string",
"description": "Optional. Pick a connected app under Settings β API & Integrations to receive your results. Notion is supported today (a run-summary page); other MCP connectors are best-effort as Apify expands its catalog."
},
"mcpIssueTeam": {
"title": "Issue tracker team",
"type": "string",
"description": "Only when the connected app is an issue tracker: the team (name or ID) the summary issue is created under, if that app requires one."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```