FINN.no Job Scraper - Norwegian Job Listings

What does FINN.no Job Scraper do?

FINN.no Job Scraper extracts structured job data from finn.no — including salary data, contact details (email, apply URL), company metadata, full descriptions, and location data. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions, company metadata, and contact information) where the source provides them.

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Key features

• ♻️ Incremental mode — recurring runs emit only NEW / UPDATED / REAPPEARED records — UNCHANGED and EXPIRED are opt-in. First run builds the baseline; subsequent runs emit and charge only for the diff. Pair with notifications for daily "new jobs" alerts to your hiring team. Saves 80–95% on daily monitoring.
• 🔔 Notifications — Telegram, Slack, Discord, WhatsApp Cloud API, generic webhook — out of the box. Pair with incremental + notifyOnlyChanges for daily "new Finn jobs" pings to your hiring channel.
• 📋 Detail enrichment — two-stage mode: list, then enrich each job with the full description + detail-page fields (apply counts, education, etc.). One toggle, no extra orchestration.
• 📧 Email + phone extraction — every record carries extractedEmails[] and extractedPhones[] regex-pulled from the description — direct-outreach lists with no extra processing step.
• 🔗 URL + social-profile extraction — every record carries extractedUrls[] and structured socialProfiles { linkedin, twitter, github, … } parsed from the description — useful when employers drop their careers page or recruiter LinkedIn in-line.
• 📦 Compact mode — AI-agent and MCP-friendly compact payloads with core fields only — pipe straight into your ATS, salary-benchmarking tool, or LLM context without parsing extras.
• ✂️ Description truncation — cap description length with descriptionMaxLength to control LLM prompt cost and dataset size — set 0 for full descriptions, or any char-limit to trim.
• 📤 Export anywhere — Download the dataset as JSON, CSV, or Excel from the Apify Console, or stream live via the Apify API and integrations (Make, Zapier, Google Sheets, n8n, …).

What data can you extract from finn.no?

Each result includes core listing fields (jobId, title, jobTitle, location, locations, coordinates, noOfPositions, labels, and more), detail fields when enrichment is enabled (description, descriptionText), contact and apply information (contactPerson, contactPhone, easyApply), and company metadata (company, employerUrl).

By default (since v0.2.0), null and empty values are dropped from each row to keep output compact for LLM pipelines. Set omitNulls: false if you need a stable schema where every row has every documented field. Enable compact: true for an even smaller payload with only core fields.

Input

The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.

Key parameters:

• query — Job search keyword (e.g. 'utvikler', 'sykepleier', 'engineer'). Leave empty to browse all jobs.
• location — Norwegian county or city (e.g. 'Oslo', 'Bergen', 'Trondheim')
• jobType — Filter by employment type (default: "fulltime")
• maxResults — Maximum number of jobs to return (0 = unlimited) (default: 25)
• fetchDetails — Fetch full job details from each listing page. Enables: description, employmentType, employerUrl, fullAddress, deadlineText, sector, industry, occupation, workLanguage, contactPerson, contactPhone, applyUrl. Adds one HTTP request per job. (default: true)
• descriptionMaxLength — Truncate job descriptions to this many characters (0 = no truncation)
• compact — Return only core fields (jobId, title, jobTitle, company, location, employmentType, publishedAt, url, description, changeType). Ideal for AI agents and MCP workflows. (default: false)
• omitNulls — Drop fields with null, empty string, empty array, or empty object values from each output row. Reduces dataset size and removes noise for LLM pipelines. Keeps false and 0 as valid values. Default on — flip off if you need a stable schema where every row has every documented field. (default: true)
• incrementalMode — Only return new or changed jobs since last run (requires stateKey) (default: false)
• stateKey — Optional stable identifier for the tracked search universe. Leave empty to auto-derive a stable identifier from your search inputs — different keyword/location/filter combinations get isolated state automatically.
• skipReposts — Exclude listings detected as reposts of previously seen jobs. (default: false)
• telegramToken — Telegram bot token from @BotFather. Required for Telegram notifications.
• ...and 10 more parameters

Input examples

Basic search — Keyword-driven search with a result cap.

→ Full payload per result — all standard fields populated where the source provides them.

{
  "query": "utvikler",
  "maxResults": 50
}

Incremental tracking — Only emit jobs that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
  "query": "utvikler",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "utvikler-tracker"
}

Compact filtered output — Combine filters with compact mode for a lightweight AI-agent or MCP data source.

→ Core fields only — ideal for piping into LLMs or downstream tools without token overhead.

{
  "query": "utvikler",
  "jobType": "fulltime",
  "maxResults": 50,
  "compact": true
}

Output

Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example job record

{
  "jobId": "458545436",
  "title": "Vi søker Software Architect for morgendagens bankløsninger",
  "jobTitle": "Software Architect",
  "company": "TIETOEVRY FINTECH NORWAY AS",
  "location": "Fornebu",
  "locations": [
    "Norge",
    "Akershus",
    "Bærum"
  ],
  "coordinates": {
    "lat": 59.8998,
    "lon": 10.62909
  },
  "noOfPositions": 1,
  "easyApply": false,
  "labels": null,
  "publishedAt": "2026-04-04T19:06:01.000Z",
  "logoUrl": "https://images.finncdn.no/dynamic/default/item/458545436/974c33a9-aca1-4721-91e7-f2c29944a056",
  "url": "https://www.finn.no/job/ad/458545436",
  "portalUrl": "https://www.finn.no",
  "description": "<p></p><p><strong>Om rollen</strong> </p><p>Tieto Banktech er midt i en omfattende moderniseringsreise, der eldre løsninger erstattes med en modulær, Java?basert arkitektur med høy grad av automatiser...",
  "descriptionText": "Om rollen \nTieto Banktech er midt i en omfattende moderniseringsreise, der eldre løsninger erstattes med en modulær, Java?basert arkitektur med høy grad av automatisering og moderne DevOps?prinsipper....",
  "employmentType": "FULL_TIME",
  "formOfEmployment": "Fast",
  "employerUrl": "https://www.tieto.com",
  "deadline": "2026-05-15",
  "deadlineText": "Snarest",
  "fullAddress": "Oslo, 1360 Fornebu",
  "sector": "Privat",
  "industry": [
    "Bank, finans og forsikring",
    "Konsulent og rådgivning",
    "IT - programvare"
  ],
  "occupations": [
    "IT utvikling / Systemarkitekt",
    "IT utvikling / Utvikler (generell)"
  ],
  "workingLanguages": null,
  "contactPerson": "Bernt Espelien",
  "contactPhone": "46 67 69 90",
  "applyUrl": null,
  "keywords": [
    "Banking as a Platform",
    "Banking Software",
    "Web backend",
    "Java",
    "Software Development"
  ],
  "aiSummary": {
    "whatWeOffer": [
      "Jobbe med samfunnskritiske løsninger",
      "Sentral rolle i utvikling av moderne bankplattformer",
      "Sterkt fagmiljø innen arkitektur, teknologi og bank",
      "Innovativt miljø med sky, AI og moderne arkitektur",
      "Konkurransedyktige betingelser og fleksible ordninger",
      "Faglig utvikling og god balanse mellom jobb og fritid"
    ],
    "qualifications": [
      "Solid bakgrunn innen moderne utvikling, gjerne Java",
      "Forståelse for arkitekturmønstre og systemdesign",
      "Evne til å se helheten og arkitekturvalgs konsekvenser",
      "Analytisk, kvalitetsbevisst og nysgjerrig",
      "Interesse for AI og nye teknologier"
    ],
    "shortDescription": "Vi søker en erfaren arkitekt til å lede moderniseringen av bankløsninger. Du vil jobbe hands-on med moderne Java, automatisering og AI."
  },
  "compensation": null,
  "scrapedAt": "2026-04-04T20:26:34.497Z",
  "changeType": null
}

Incremental fields

When incremental: true, each record also carries:

• changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED.
• firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.
• isRepost, repostOfId, repostDetectedAt — populated when a new listing matches the tracked content of a previously expired one. Set skipReposts: true to drop detected reposts from the output.

How to scrape finn.no

1. Go to FINN.no Job Scraper in Apify Console.
2. Enter a search keyword and optional location filter.
3. Set maxResults to control how many results you need.
4. Enable fetchDetails if you need full descriptions, contact info, company data.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract job data from finn.no for market research and competitive analysis.
• Track pricing trends across regions and categories over time.
• Monitor new and changed listings on scheduled runs without processing the full dataset every time.
• Build outreach lists using contact details and apply URLs from listings.
• Research company hiring patterns, employer profiles, and industry distribution.
• Use structured location data for regional analysis, mapping, and geo-targeting.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.

How much does it cost to scrape finn.no?

FINN.no Job Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.005 per run
• Per result: $0.0015 per job record

Example costs:

• 10 results: $0.02
• 100 results: $0.15
• 500 results: $0.76

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 100 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.15	$0.01	$0.14 (92%)	$0.38
15% — moderate broad query	$0.15	$0.03	$0.13 (82%)	$0.82
30% — high-volume aggregator	$0.15	$0.05	$0.11 (68%)	$1.50

Full re-scrape monthly cost at daily polling: $4.65. First month with incremental costs $0.52 / $0.95 / $1.60 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

FAQ

How many results can I get from finn.no?

The number of results depends on the search query and available listings on finn.no. Use the maxResults parameter to control how many results are returned per run.

Does FINN.no Job Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate FINN.no Job Scraper with other apps?

Yes. FINN.no Job Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use FINN.no Job Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use FINN.no Job Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

Is it legal to scrape finn.no?

This actor extracts publicly available data from finn.no. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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Getting started with Apify

New to Apify? Create a free account with $5 credit — no credit card required.

1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click Start — export results as JSON, CSV, or Excel

Need more later? See Apify pricing.