💼 LinkedIn Jobs Scraper | $3/1K | Salary, Skills, Recruiter Score

Real-time LinkedIn Jobs scraper plus 12 layers of recruitment intelligence: salary parser (USD-normalized), job freshness, work-mode classifier (remote/hybrid/onsite), 200+ skills extraction, benefits parser (401k/equity/visa/...), seniority normalizer, job category auto-detect, recruiterScore 0-100, industry-specific outreach pitches, and one-click outreach links — all in one $0.003/job call.

Built for recruitment-tech, ATS, sourcing tools, HR-tech B2B sales, competitive intelligence, and salary benchmarking.

✨ What you get for $0.003 per job

⭐ Core (LinkedIn)

• Job title, company name, location
• Job type, description snippet, posted date, company logo
• Direct job URL

💰 Salary parser

• salaryMinUsd, salaryMaxUsd, salaryMedianUsd — USD-normalized
• salaryPeriod (hour/day/week/month/year) — auto-detected
• salaryCurrency — USD/EUR/GBP/CAD/AUD/INR/JPY (FX converted)
• Hourly/daily/weekly/monthly auto-annualized to year
• salaryRaw for verification, salary_is_estimate flag

⏱️ Job freshness

• daysSincePosted — Posted 3 days ago → 3
• freshness_tier — today / this_week / this_month / older

🌍 Work-mode classifier

• workMode — remote / hybrid / onsite / unknown
• workMode_signals[] — keywords that triggered classification

🛠️ Skills extraction (200+ tech terms)

• skillsRequired[] — Python, React, Postgres, AWS, Kubernetes, GraphQL, TensorFlow, LangChain, Salesforce, Shopify, ...
• skillsCount
• softSkills[] — leadership, communication, mentoring, ...
• certifications[] — AWS / Azure / GCP / CKAD / PMP / CISSP / ...

🎁 Benefits parser — 14 boolean flags

mentions_401k, mentions_health_insurance, mentions_equity, mentions_remote_work, mentions_visa_sponsorship, mentions_relocation, mentions_unlimited_pto, mentions_parental_leave, mentions_signing_bonus, mentions_4_day_week, mentions_stipend, mentions_meals, mentions_gym, mentions_commuter_benefits, plus benefitsCount

🎯 Seniority normalizer

intern / junior / mid / senior / lead / staff / principal / director / vp / c-level / unspecified. Reliable across noisy titles (Sr SWE / Senior Software Engineer / SWE III all map to senior).

🏷️ Job category auto-detect

engineering / data_science / product / design / sales / marketing / finance / hr / operations / legal / customer_support / healthcare / education / construction_trades / other

🎯 recruiterScore (0-100) + tier + reasons

• B2B prospecting score for recruitment-tech / ATS / sourcing-tool / HR-tech sales. Combines:
  • Number of roles open at same company in this run (active budget)
  • Job freshness (active demand)
  • Salary disclosed + tier
  • Modern skills count, benefits depth
  • Decision-maker seniority (VP/director/C-level = budget owner)
  • Remote-friendly / visa sponsorship (talent strategy)
• recruiterTier — cold / warm / hot / scorching
• recruiterScoreReasons[] — explainable signals

📞 One-click outreach links

• linkedin_company_url
• linkedin_jobs_at_company_url
• linkedin_hiring_manager_search_url — pre-filtered "VP of engineering / head of talent / hiring manager" search
• google_search_url
• careers_page_guess

💬 Industry-specific outreach pitch (per company)

Written to the TOP_HIRING_COMPANIES KV record. 8 industry templates covering engineering, data/AI, sales, marketing, product, design, finance, HR/talent.

📊 SUMMARY + TOP_HIRING_COMPANIES (free aggregates)

On bulk runs, two records are written to the run's KV store (free — doesn't trigger pay-per-event):

SUMMARY:

• avg/p25/p75 salary across the run
• by_category / by_seniority / by_work_mode / by_freshness
• by_recruiter_tier
• top_companies, top_skills_demanded, top_benefits_offered
• salary_disclosed_pct, remote_friendly_pct, fresh_today_count

TOP_HIRING_COMPANIES:

• Top 20 companies sorted by job count
• Per-company: jobs_count, max_recruiterScore, categories, top_skills, avg_salary_usd, outreachPitch, outreachLinks
• Drop into Slack as a daily sales digest

📦 Input

Basic

{
  "keywords": "software engineer",
  "location": "United States",
  "maxPages": 3
}

Recruitment-tech B2B prospecting (recommended preset)

{
  "keywords": "engineering manager",
  "location": "United States",
  "maxPages": 10,
  "remote": true,
  "experienceLevel": "director",
  "minRecruiterScore": 60,
  "onlyWithSalary": true,
  "exportFormat": "csv"
}

This returns only director-level engineering managers at remote-friendly companies disclosing salary with recruiterScore ≥ 60 — perfect for selling sourcing tools.

Salary benchmarking (Bay Area senior engineers)

{
  "keywords": "senior software engineer",
  "location": "San Francisco Bay Area",
  "maxPages": 15,
  "experienceLevel": "mid_senior",
  "onlyWithSalary": true
}

All input parameters

Field	Type	Default	Description
keywords	string	required	Job title or keywords
location	string	—	City / country / 'Remote'
maxPages	int	3	1-15. ~25 jobs/page.
remote	bool	false	LinkedIn f_WT=2 filter
experienceLevel	string	any	internship/entry/associate/mid_senior/director/executive
jobType	string	any	full_time/part_time/contract/temporary/volunteer/internship
postedWithin	string	any	day/week/month
extractSalary	bool	true	Salary raw text
extractSalaryParse	bool	true	Salary → USD numeric
extractFreshness	bool	true	daysSincePosted + tier
extractWorkMode	bool	true	remote/hybrid/onsite
extractSkills	bool	true	200+ skills regex
extractBenefits	bool	true	14 benefit flags
extractSeniority	bool	true	intern→c-level normalization
extractCategory	bool	true	jobCategory auto-detect
extractRecruiterScore	bool	true	0-100 + tier + reasons
extractOutreachAssets	bool	true	outreachLinks + pitches
deduplicateCompanies	bool	false	One job per company
minRecruiterScore	int	0	Drop below threshold
onlyWithSalary	bool	false	Comp-transparent only
onlyRemote	bool	false	Fully-remote only
exportFormat	enum	default	default / csv
writeSummary	bool	true	KV aggregates
topCompaniesN	int	20	TOP_HIRING_COMPANIES size
maxRetries	int	1	Retry on transient failures
maxConcurrency	int	2	Parallel page scrapes
timeout	int	120	Seconds per page

📖 Sample Output

{
  "success": true,
  "source": "linkedin",
  "jobTitle": "Senior Backend Engineer",
  "companyName": "Acme Corp",
  "location": "San Francisco, CA (Remote)",
  "jobType": "Full-time",
  "description": "Build the next-gen data platform with Python, FastAPI, Postgres, Kubernetes. Comp $180K-$240K + equity, 401k 6% match, unlimited PTO, $2K learning stipend...",
  "postedDate": "3 days ago",
  "jobUrl": "https://www.linkedin.com/jobs/view/3712345678",

  "salaryMinUsd": 180000,
  "salaryMaxUsd": 240000,
  "salaryMedianUsd": 210000,
  "salaryPeriod": "year",
  "salaryCurrency": "USD",

  "daysSincePosted": 3,
  "freshness_tier": "this_week",

  "workMode": "remote",
  "workMode_signals": ["+remote"],

  "skillsRequired": ["Python", "Fastapi", "Postgres", "Kubernetes"],
  "skillsCount": 4,

  "mentions_equity": true,
  "mentions_401k": true,
  "mentions_unlimited_pto": true,
  "mentions_stipend": true,
  "mentions_remote_work": true,
  "benefitsCount": 5,

  "seniority_normalized": "senior",
  "jobCategory": "engineering",

  "recruiterScore": 73,
  "recruiterTier": "hot",
  "recruiterScoreReasons": [
    "5 roles open",
    "posted this week",
    "salary disclosed",
    "high-tier comp",
    "5 benefits listed",
    "remote-friendly"
  ],

  "outreachLinks": {
    "linkedin_company_url": "https://www.linkedin.com/company/Acme+Corp",
    "linkedin_hiring_manager_search_url": "https://www.linkedin.com/search/results/people/?keywords=Acme+Corp+%22hiring+manager%22+OR+...",
    "google_search_url": "https://www.google.com/search?q=%22Acme+Corp%22+careers",
    "careers_page_guess": "https://acmecorp.com/careers"
  }
}

💼 Use cases

🥇 Recruitment-tech / ATS / sourcing-tool B2B sales

• Filter recruiterTier = "scorching" for warmest accounts
• Filter seniority_normalized in (vp, director, c-level) for budget owners
• Filter jobCategory = "hr" for talent-acquisition leaders themselves
• Use outreachLinks.linkedin_hiring_manager_search_url to find the buyer
• Use TOP_HIRING_COMPANIES per-company outreachPitch as the first cold-email draft

💰 Salary benchmarking

• salaryMedianUsd normalized across hourly/yearly/EUR/GBP
• Aggregate by seniority_normalized, jobCategory, workMode, location
• SUMMARY.salary_p25_usd / p75_usd for percentile bands

📈 Hiring trends / market research

• daysSincePosted distribution = real-time labor demand
• top_skills_demanded from SUMMARY = what skills companies are paying for
• mentions_visa_sponsorship % = global talent strategy adoption

🔍 Competitive intelligence

• Track which roles your competitors are hiring for
• top_companies from SUMMARY = density per query
• mentions_equity % across competitors = comp benchmarking

👥 Job aggregator / niche board

• Filter freshness_tier = "today" for daily fresh listings
• Filter workMode = "remote" for remote job boards
• Filter jobCategory = "engineering" for vertical boards

💰 Pricing

Volume	Cost
1 job	$0.003
100	$0.30
1,000	$3.00
10,000	$30.00

Pay only for what you extract. No subscriptions, no API keys.

⚡ How it works

1. Build LinkedIn Jobs public search URL with your filters
2. Paginate ?start=0&start=25&start=50...
3. Each page through a real-time rendering engine on Apify infrastructure
4. Dedupe by title+company+location fingerprint
5. Two-pass enrichment: collect all rows, compute per-company hiring count, then enrich every job with all 12 layers including the recruiterScore
6. Apply post-filters (minRecruiterScore, onlyWithSalary, onlyRemote)
7. Write SUMMARY + TOP_HIRING_COMPANIES to KV store (free)

Typical coverage:

• 1 page → ~25 jobs
• 3 pages → ~60-75 jobs
• 10 pages → ~200-250 jobs

❓ FAQ

Q: Do I need a LinkedIn account? A: No. The actor scrapes the public job search results — no login required.

Q: How accurate is the salary parser? A: Recognizes ranges, single values, K/M suffixes, and 7 currencies. Handles hourly/weekly/monthly auto-annualization. Falls back to scanning the description text. Cases where LinkedIn doesn't display salary at all return null (silently — use onlyWithSalary: true to drop them).

Q: How accurate is recruiterScore? A: It's a heuristic — bigger hiring-active companies with senior roles, fresh postings, and disclosed salaries score highest. Treat scorching/hot as priority outreach, warm as nurture, cold as deprioritize.

Q: Will it work for jobs in non-English markets? A: Yes — but the skills/benefits parsers are tuned to English keywords. Salary parser handles EUR/GBP/CAD/AUD/INR/JPY currencies; non-English postings still get core fields + salary if the listing has a numeric range.

Q: Can I filter by salary range? A: Use minRecruiterScore (which factors in salary tier), or filter client-side after the run with salaryMedianUsd.

🔗 Related Actors

• Indeed Jobs Scraper — Indeed's job listings
• Glassdoor Jobs Scraper — Glassdoor jobs
• LinkedIn Profile Scraper — Public profile data
• Job Posting Lead Finder — Multi-board job lead aggregator
• Yelp Business Analyzer — Local business intelligence

📞 Support

Open an issue on the actor's Apify page or message via Apify.