JobSignal — LinkedIn Job Intelligence API for Apify

JobSignal converts public LinkedIn job listings into clean, enriched, analytics-ready data. It is a cost-efficient TypeScript/Crawlee Apify Actor designed for job boards, recruiting intelligence, lead generation, market research, and automated alerts.

It goes beyond copying HTML:

• Searches by role, skill, location, recency, workplace type, seniority, and contract type.
• Accepts direct public LinkedIn job URLs and search URLs.
• Extracts clean descriptions, company, location, employment type, post date, applicant count, and Easy Apply status.
• Normalizes disclosed hourly, monthly, and annual salary ranges.
• Detects common technical and business skills plus benefits.
• Infers remote/hybrid/on-site status and seniority.
• Generates a stable fingerprint for cross-run deduplication and change tracking.
• Adds matchScore and dataQualityScore fields.
• Produces a run-level market summary with top skills, top companies, remote share, and salary coverage.
• Exports through Apify Dataset API as JSON, CSV, Excel, XML, or RSS.

Why TypeScript + Crawlee

Apify gives Node.js and TypeScript first-class support. Crawlee supplies production request queues, retries, autoscaling, session/proxy integration, and local/Apify storage with minimal runtime overhead. This Actor deliberately uses HTTP + Cheerio instead of a browser, making typical runs substantially faster and cheaper than Playwright-based scrapers.

Quick start

Requires Node.js 22+.

npm install
npm run build
npm test

Run locally with Apify CLI:

$apify run

Or create storage/key_value_stores/default/INPUT.json and run:

$npm run dev

Example input:

{
  "searchQueries": ["TypeScript engineer", "AI engineer"],
  "locations": ["United States", "Bengaluru, Karnataka, India"],
  "maxJobs": 250,
  "postedWithin": "pastWeek",
  "workplaceTypes": ["remote", "hybrid"],
  "experienceLevels": ["entry", "mid-senior"],
  "jobTypes": ["full-time", "contract"],
  "includeKeywords": ["LLM", "TypeScript", "Python"],
  "excludeKeywords": ["clearance required"],
  "deduplicate": true,
  "enrichResults": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Use as an API

After deploying the Actor, start a run and return dataset items synchronously:

curl -X POST \
  "https://api.apify.com/v2/acts/YOUR_USERNAME~linkedin-job-intelligence-api/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN&format=json" \
  -H "Content-Type: application/json" \
  -d '{
    "searchQueries": ["backend engineer"],
    "locations": ["London"],
    "maxJobs": 50,
    "postedWithin": "past24h"
  }'

For larger runs, use the asynchronous endpoint:

curl -X POST \
  "https://api.apify.com/v2/acts/YOUR_USERNAME~linkedin-job-intelligence-api/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQueries":["data engineer"],"locations":["Germany"],"maxJobs":500}'

Then retrieve:

• Jobs: GET https://api.apify.com/v2/datasets/{defaultDatasetId}/items
• Summary: GET https://api.apify.com/v2/key-value-stores/{defaultKeyValueStoreId}/records/OUTPUT

Keep tokens in secrets or environment variables; never embed them in client-side applications.

Output record

{
  "id": "123456789",
  "url": "https://www.linkedin.com/jobs/view/123456789",
  "title": "Senior TypeScript Engineer (Remote)",
  "company": "Acme Labs",
  "location": "Bengaluru, India",
  "workplaceType": "remote",
  "employmentType": "Full-time",
  "seniority": "mid-senior",
  "postedAt": "2026-07-25T00:00:00.000Z",
  "descriptionText": "...",
  "salary": {
    "raw": "USD 120,000 - 160,000 per year",
    "min": 120000,
    "max": 160000,
    "currency": "USD",
    "period": "year",
    "annualizedMin": 120000,
    "annualizedMax": 160000
  },
  "skills": ["TypeScript", "React", "Node.js", "AWS"],
  "benefits": ["Health insurance", "Equity"],
  "fingerprint": "d24f...",
  "matchScore": 55,
  "dataQualityScore": 95,
  "source": "linkedin-public"
}

Salary parsing only reports a currency when it is stated or represented by an unambiguous symbol. JobSignal does not silently perform foreign-exchange conversion.

Standout workflows

New-job alerts

Schedule the Actor hourly or daily. Store the fingerprint values from the prior dataset and alert only on unseen values with an Apify webhook, Make, Zapier, Slack, or email integration.

Skills demand radar

Read OUTPUT.topSkills after each scheduled run and store snapshots. The series reveals which tools are gaining or losing demand for a role and location.

Salary transparency benchmark

Set minimumSalary and salaryCurrency for precise compensation searches. salaryCoverage in the run summary shows how representative the disclosed-salary subset is.

ATS / CRM ingestion

Use the stable schema and fingerprints as idempotency keys when writing records to an ATS, CRM, database, or data warehouse.

Reliability and responsible use

LinkedIn can change its public HTML and rate limits without notice. Production users should:

• Use Apify residential proxies and conservative concurrency.
• Keep retries enabled and schedule smaller incremental runs.
• Monitor failedRequests and dataQualityScore.
• Update selectors and fixture tests when source markup changes.

To satisfy post-extraction filters without returning a thin result set, JobSignal may inspect up to three times maxJobs candidates (capped at 5,000) and stops writing as soon as maxJobs accepted records are reached.

This Actor accesses public job pages only. It does not log in, solve CAPTCHAs, scrape profiles, or bypass access controls. You are responsible for ensuring that your use complies with LinkedIn's terms, robots rules, privacy laws, employment laws, and the rules applicable in your jurisdiction. Collect only data you have a lawful reason to process, respect deletion requests, and avoid discriminatory hiring uses.

Architecture

Input schema
    │
    ├── search query + filters ──> public search result pages
    └── direct URL ──────────────> public job detail page
                                      │
                                      v
                          parse + normalize + enrich
                                      │
                         filter + fingerprint + dedupe
                                ┌─────┴─────┐
                                v           v
                         Dataset jobs   OUTPUT summary

Deploy to Apify

1. Install and authenticate the Apify CLI: npm install -g apify-cli then apify login.
2. From this folder, run apify push.
3. In Apify Console, select a suitable proxy configuration and test a small run.
4. Add a schedule/webhook if you need recurring feeds.
5. Before publishing in Apify Store, add screenshots, pricing, support details, and validate the Actor against current public markup.

The project includes an Actor definition, input/output schemas, two dataset views, a multi-stage production Dockerfile, and deterministic unit/fixture tests.

License

MIT. LinkedIn is a trademark of LinkedIn Corporation. This project is independent and is not affiliated with or endorsed by LinkedIn.