LinkedIn Jobs: scrapers and the official API, compared

Route map

Each line is one way to get LinkedIn Jobs data; each stop is a field you probably need. Green lines are catalogue Actors, ranked by the published formula.

Field matrix: who returns what

Every tool with a published output schema, against the 7 fields most LinkedIn Jobs jobs need. A dot means the field name appears in the schema; rows can still leave it empty.

Field dictionary: the exact keys

The same core field has a different key in each Actor's output. Map these before you merge datasets; a dash means the published schema has no matching key. Need a field that is not listed here, such as email? Search every LinkedIn Jobs Actor by field.

Download this comparison: CSV · JSON (every tool with a published schema, matching keys per core field, price and score).

All 9 tools, scored

Catalogue Actors link to their detail pages; the score (0 to 100) is the published formula, identical for every tool. Other Store tools follow in their own table, for reference. Price is the published primary-result rate per 1,000 (the Free-plan rate where the price is tiered; higher Apify plans pay less); start events and platform usage are excluded.

Other Store tools, for reference

Scored with the same published formula and listed for comparison only; this site does not link or recommend them.

What to check before you choose

LinkedIn job postings help hiring teams track employer demand, compare advertised roles and examine compensation where salaries are listed. Location, seniority and employment type can help separate comparable openings before drawing conclusions about a hiring market.

Approved talent partners can pursue access through LinkedIn Talent APIs, subject to contractual scope. For public posting research, compare scraping tools by their published output; LinkedIn Jobs Scraper with Salary & Company Enrichment includes company context and salary-related attributes for employer and compensation comparisons.

Checklist

• Check how the published schema maps to your destination: companyName, postedDate and jobUrl use different names from company, posted_at and url.
• Inspect salarySource alongside salary and salaryRange.currency before comparing compensation.
• Confirm that descriptions are available if you need skills or responsibilities. The published schema for LinkedIn Jobs Scraper with Salary & Company Enrichment does not list description.

Where the data is incomplete

Salary details depend on what a posting contains and what enrichment returns.

The published schema includes postedDate and expiresAt. Without example records, completeness, date formatting and consistency across job and company attributes remain unconfirmed.

Official API route

Terms and personal data

Limit collection to public job pages and review LinkedIn's terms before automating access. Public visibility is not permission for collection or reuse. This is general information, not legal advice.

Read LinkedIn Jobs' terms. Keep to public data, do not bypass logins or access controls, and check whether personal data is involved before you collect it. The can-I-scrape checklist walks through it.

How to start

1. Open the Store listing for LinkedIn Jobs Scraper with Salary & Company Enrichment and review its documented inputs and event charges.
2. Configure a narrow job search using the supported inputs, then start an initial collection.
3. Inspect the resulting dataset for title, companyName, location, postedDate and jobUrl, then check salarySource and missing values before expanding collection.

Call LinkedIn Jobs Scraper with Salary & Company Enrichment from code

The example input uses the Actor's published defaults; set your own LinkedIn Jobs query before you run it. You need an Apify API token.

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run_input = {
    "searchQueries": [
        "Python Developer"
    ],
    "locations": [
        "United States"
    ],
    "easyApply": False,
    "under10Applicants": False,
    "industry": [],
    "companySizes": [],
    "excludeStaffingAgencies": False,
    "requireSalary": False,
    "requireRecruiter": False,
    "scrapeJobDetails": False,
    "includeCompanyDetails": False,
    "enrichmentDepth": "standard",
    "language": "en",
    "splitLargeSearches": True,
    "maxItems": 3
}

run = client.actor("nimbryxo-studio/linkedin-jobs-scraper-with-salary-and-company").call(run_input=run_input)
if run is None:
    raise RuntimeError("The Actor run was not found.")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });
const input = {
    "searchQueries": [
        "Python Developer"
    ],
    "locations": [
        "United States"
    ],
    "easyApply": false,
    "under10Applicants": false,
    "industry": [],
    "companySizes": [],
    "excludeStaffingAgencies": false,
    "requireSalary": false,
    "requireRecruiter": false,
    "scrapeJobDetails": false,
    "includeCompanyDetails": false,
    "enrichmentDepth": "standard",
    "language": "en",
    "splitLargeSearches": true,
    "maxItems": 3
};

const run = await client.actor("nimbryxo-studio/linkedin-jobs-scraper-with-salary-and-company").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

curl -X POST "https://api.apify.com/v2/actors/nimbryxo-studio~linkedin-jobs-scraper-with-salary-and-company/run-sync-get-dataset-items"   -H "Authorization: Bearer $APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"searchQueries":["Python Developer"],"locations":["United States"],"easyApply":false,"under10Applicants":false,"industry":[],"companySizes":[],"excludeStaffingAgencies":false,"requireSalary":false,"requireRecruiter":false,"scrapeJobDetails":false,"includeCompanyDetails":false,"enrichmentDepth":"standard","language":"en","splitLargeSearches":true,"maxItems":3}'

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=nimbryxo-studio/linkedin-jobs-scraper-with-salary-and-company",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Questions people ask

More on LinkedIn Jobs

• Error fixHTTP 999 from LinkedIn: what the non-standard status means
• Topic groupJobs and hiring data: every website compared
• ToolWhich LinkedIn Jobs route fits your job?
• ToolLinkedIn Jobs cost by Apify plan, rows and runs

Related websites

• LinkedIn19 Actors
• Indeed2 Actors
• Glassdoor2 Actors

Sources

• LinkedIn Jobs Scraper with Salary & Company Enrichment on Apify Store
• LinkedIn Talent APIs documentation
• LinkedIn Jobs terms