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LinkedIn Jobs Scraper Pro v2

Production-grade LinkedIn job scraper. Multi-keyword, multi-location, JSON-LD enrichment, parallel detail fetch, real typed fields, dedup, XLSX/CSV/JSON export.

👁 LinkedIn Jobs Scraper Pro

What it does

Search LinkedIn by job title × location and return a clean, enriched dataset. Every row includes the basics (title, company, location, date, Easy Apply, URL) plus the fields that actually matter for recruiting, sourcing, and market research:

• Salary (salaryMin, salaryMax, salaryCurrency, salaryUnit, salaryRaw) — parsed from JSON-LD baseSalary or inline ranges
• Company enrichment (companyUrl, companySlug, companyLogoUrl) — from JSON-LD hiringOrganization or card HTML
• Job classification (industry, jobFunction, experienceLevel, employmentType)
• Applicants — applicantsCount is an integer (47), applicantsRaw is the original text ("47 applicants")
• Recency (postedDate, postedTimeAgo, isNew, badge)
• Full description (jobDescription) + optional descriptionHtml
• Direct apply flag (directApply, easyApply as booleans)
• Search provenance (searchKeyword, searchLocation, scrapedAt)

Pricing

$0.50 per 1,000 jobs (pay per result, no monthly minimum).

Compared to:

• valig/linkedin-jobs-scraper: $0.40/1k — cheaper per job, more fields, parallel fetch
• bebity/linkedin-jobs-scraper: $15–29.99/month flat — no per-job pricing, capped by month

How it works

1. Phase 1 — listing scrape (guest API): pulls cards from linkedin.com/jobs-guest/jobs/api/seeMoreJobPostings/search for every (title × location) combo. No login, no auth wall.
2. Dedup by jobId across the whole run.
3. Phase 2 — parallel detail fetch with asyncio.gather + asyncio.Semaphore(concurrency). Each detail page is parsed for JobPosting JSON-LD (most rich fields live here) and BeautifulSoup is used for fields JSON-LD doesn't carry (applicants, seniority, Easy Apply button).
4. Optional XLSX/CSV export to the run's Key-Value Store.
5. Push to dataset with strict typing: bools are bools, counts are ints, missing data is null.

Input

Example input

{
"job_titles":["Head of Engineering","VP of Technology","Delivery Director"],
"locations":["India","United States","United Kingdom"],
"days_posted":30,
"max_jobs_per_keyword":50,
"seniority_levels":"5,6",
"work_type":"2",
"fetch_job_details":true,
"use_apify_proxy":true,
"concurrency":8,
"output_format":"all"
}

Example output

{
"jobId":"4418924625",
"title":"Senior Director, AI Product Operations & Solutions",
"company":"Blue Machines AI",
"companyUrl":"https://www.linkedin.com/company/blue-machines-ai",
"companySlug":"blue-machines-ai",
"companyLogoUrl":"https://media.licdn.com/.../blue_machines_ai_logo",
"location":"Mumbai, Maharashtra, India",
"postedDate":"2026-05-26T08:00:00.000Z",
"postedTimeAgo":"1 day ago",
"isNew":true,
"badge":"Actively Hiring",
"salaryMin":5000000,
"salaryMax":8000000,
"salaryCurrency":"₹",
"salaryUnit":"year",
"salaryRaw":"₹50,00,000 - ₹80,00,000 a year",
"easyApply":false,
"remoteHybrid":false,
"employmentType":"Full-time",
"experienceLevel":"Director",
"jobFunction":"Information Technology",
"industry":"Software Development",
"applicantsCount":47,
"applicantsRaw":"47 applicants",
"validThrough":"2026-07-26T00:00:00.000Z",
"directApply":false,
"jobDescription":"We are looking for a Senior Director...",
"jobUrl":"https://in.linkedin.com/jobs/view/4418924625",
"searchKeyword":"Delivery Director",
"searchLocation":"India",
"scrapedAt":"2026-06-23T10:15:00.000Z"
}

Output formats

• JSON — always pushed to the dataset. Pipe straight to apify-client, BigQuery, or a NoSQL store.
• XLSX — written to the run's Key-Value Store as jobs-<runId>.xlsx when output_format=xlsx or all. Opens in Excel/Sheets with auto-typed columns.
• CSV — written to the run's Key-Value Store as jobs-<runId>.csv when output_format=csv or all.

Performance

Limitations

• LinkedIn's guest API is unauthenticated. The card HTML is reliable; the detail HTML occasionally hits a soft auth wall (job is then pushed with jobDescription="" and the URL is preserved).
• Some fields (salary, applicants) are not on every posting — nulls are expected.
• LinkedIn rotates its HTML classes; this version pins the Q2 2026 class set and falls back to JSON-LD for resilience.

License & ToS

This actor is for personal use, research, and licensed commercial use. Respect LinkedIn's ToS and applicable data-protection laws (GDPR, etc.) when storing personal data.