LinkedIn Fresh Jobs Scraper

What does LinkedIn Fresh Jobs Scraper do?

LinkedIn Fresh Jobs Scraper collects public LinkedIn job postings and keeps the newest roles easy to route into a recruiting alert, job board, or hiring-intent workflow. Search by job keywords and locations, or paste a LinkedIn jobs search URL, then apply a visible posted-hours cutoff before records are written.

What data can you extract from LinkedIn jobs?

• Job identity — jobId, title, and a clean public jobUrl
• Hiring company — companyName, companyUrl, and companyLogoUrl
• Location and workplace — location and workplaceType when the source shows it or the search selected Remote
• Freshness — postedDate, postedLabel, and numeric postedAgeHours
• Run context — searchQuery, sourceUrl, scrapedAt, and the visible isEasyApply marker

The result is one flat record per unique job ID. Salary, full descriptions, applicant totals, and private recruiter profiles are outside this focused search-card feed.

How to use LinkedIn Fresh Jobs Scraper

1. Open LinkedIn Fresh Jobs Scraper and enter job keywords such as data engineer.
2. Add one or more locations, or paste a public LinkedIn jobs search URL for native filters.
3. Select a source date window, set postedWithinHours to 24 for a daily alert, and choose a maximum job count.
4. Click Run. The actor deduplicates job IDs across searches and writes only records that pass the freshness and optional Easy Apply filters.
5. Open the Dataset tab and download JSON, CSV, or Excel, or read the dataset through the Apify API.

How much does it cost?

LinkedIn Fresh Jobs Scraper uses pay-per-event pricing: $0.0015 per emitted job, or $1.50 / 1,000 jobs, plus a $0.003 actor-start event per run. The start event covers the fixed platform work even when a freshness filter writes zero records. There is no actor-specific free quota; Apify applies your account's standard credits and limits. Use postedWithinHours, maxPages, and maxJobs to keep scheduled feeds small.

Input

Use keywords with locations for generated searches, or use searchUrls when you already configured LinkedIn filters. datePosted sets a source-side window, while postedWithinHours applies a second local cutoff to the visible relative age.

{
  "keywords": ["data engineer"],
  "locations": ["United States"],
  "datePosted": "past24Hours",
  "postedWithinHours": 24,
  "remoteOnly": true,
  "sortBy": "date",
  "maxJobs": 25,
  "maxPages": 1
}

Output

Each output row contains job identity, title, company, location, workplace, posting date, freshness age, and public URLs. Nullable fields remain null when a search card does not expose them.

{
  "jobId": "4459042474",
  "title": "Data Engineer II",
  "companyName": "DriveWealth",
  "companyUrl": "https://www.linkedin.com/company/drivewealth",
  "companyLogoUrl": "https://media.licdn.com/dms/image/v2/D560BAQEgp99HhrE7yQ/company-logo_100_100/B56Z9HBYVVGQAM-/0/1783602972214/drivewealth_logo",
  "location": "New York, NY",
  "workplaceType": "remote",
  "postedDate": "2026-08-25",
  "postedLabel": "21 hours ago",
  "postedAgeHours": 21,
  "jobUrl": "https://www.linkedin.com/jobs/view/data-engineer-ii-at-drivewealth-4459042474",
  "searchQuery": "data engineer",
  "sourceUrl": "https://www.linkedin.com/jobs/search/?keywords=data%20engineer&location=United%20States&f_TPR=r86400&f_WT=2",
  "scrapedAt": "2026-08-26T18:00:00.000Z",
  "isEasyApply": null
}

Integrations

Schedule the actor and send new job rows to Make, n8n, Zapier, Google Sheets, Slack, or a webhook. For custom workflows, trigger it with the Apify API and consume the default dataset in Python or Node.js.

Related actors

• Greenhouse Jobs Scraper — collect structured roles from companies using Greenhouse.
• Ashby Jobs Scraper — collect public roles from Ashby boards with board-level filters.
• Indeed Jobs Scraper — broaden a job feed with Indeed search results.

FAQ

How does LinkedIn Fresh Jobs Scraper work?

It reads the public LinkedIn jobs search page returned to logged-out visitors, extracts the structured search cards, normalizes their links and dates, deduplicates job IDs, and applies local freshness checks before writing.

Can I use LinkedIn Fresh Jobs Scraper as an API?

Yes. Start a run with the Apify API, then read the default dataset items endpoint from the run response. The same dataset can be exported as JSON, CSV, or Excel in the Apify Console.

Can I use LinkedIn Fresh Jobs Scraper in Python or Node.js?

Yes. Use the official apify-client package, pass the same JSON input shown above, and iterate over the run's default dataset.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('schnellscrapers/linkedin-fresh-jobs-scraper').call({
  keywords: ['data engineer'],
  locations: ['United States'],
  postedWithinHours: 24,
  maxJobs: 25
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Is it legal to scrape LinkedIn jobs?

This actor reads public job-posting cards and does not request a login or private profile data. Laws and platform rules vary by use case and location, so review the applicable requirements before using the output; this listing is not legal advice.

Does the actor fetch full job descriptions or salaries?

No. It stays on the search-card path so fresh job feeds use one lightweight request per page. Use the public jobUrl to open a posting separately when more detail is needed.

How can I build a daily new-job alert?

Schedule a run with datePosted: "past24Hours", postedWithinHours: 24, and sortBy: "date". Send the dataset to your alerting or ATS workflow and use jobId to deduplicate notifications.

Your feedback

If a LinkedIn search layout changes or you need another business field, report it through the Issues tab on the actor page. Feature requests for additional job filters and output fields are welcome.