Welcome to the Jungle Jobs Scraper

💼 What is Welcome to the Jungle Jobs Scraper?

Welcome to the Jungle Jobs Scraper helps recruiters, HR and salary analysts, job-board builders, market researchers and sales teams with job market research, salary benchmarking and lead generation on Welcome to the Jungle (WTTJ). It extracts public job listings by keyword search with filters or from direct job links, with the salary, contract type, remote policy, skills, apply link and hiring company's profile for each job. Just type a search term (or leave it empty) and click Start, with no coding or login needed; a run saves up to 100 results by default (you can raise that or set 0 for no result limit). You can try it on the Apify Free plan, which includes $5 of monthly credit.

This Welcome to the Jungle scraper saves one structured record per job, including the full listing text, so you don't have to copy listings by hand. Download the results in JSON, CSV, Excel, XML or HTML.

• 💼 Recruiting and talent market intelligence: track which companies hire for a role, in which city, with which contract type and remote policy.
• 💲 Salary benchmarking data: run a salary comparison by role, seniority, location or company size, based on the pay that employers disclose.
• 📊 Job market analysis: measure hiring demand by job category, industry sector, contract type and remote policy.
• 🆚 Competitor hiring analysis: type a competitor's name in Search Query to see which roles it's hiring for, where, and on which contracts.
• 🧲 Lead generation: find companies that are hiring right now, with their website, LinkedIn page, size and industry.
• 📰 Job aggregator and niche job boards: feed your own site with current Welcome to the Jungle job postings and their apply links, including early-career boards (pick Internship, Apprenticeship / Work-study or Graduate program under Contract Type).

What can Welcome to the Jungle Jobs Scraper do?

• 🔍 Search Welcome to the Jungle jobs by keyword, optionally matching job titles only
• 🎯 Filter results by location and radius, country, posting date, contract type, remote policy, industry sector, job category, experience, minimum salary, company size and job content language
• 🔗 Scrape direct job links in bulk when you already know which listings you want
• 📝 Add full details for every job: description, candidate profile, skills, tools, benefits, recruitment process, apply link and an extended company profile
• 🌐 Choose a regional site for labels and URLs (English, French, Spanish, Czech or Slovak)
• 📦 Export the data to JSON, CSV, Excel, XML or HTML, or fetch it through the Apify API as your own WTTJ jobs API
• ⚙️ Run it on the Apify platform: scheduling, monitoring, webhooks, integrations and Apify Proxy support

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📊 What data can Welcome to the Jungle Jobs Scraper extract?

Every record combines Welcome to the Jungle job data with Welcome to the Jungle company data. Each record has the same 80 fields, so the WTTJ data has the same fields for every job. A few fields (offices, skills, tools, benefits) hold lists with several values per job.

Job	Company
📝 Job title title	🏢 Company name companyName
🔗 Job URL url and apply link applyUrl	🌐 Company website companyWebsite and page companyUrl
📄 Contract type contractType, contractTypeName	👥 Company size companySize, companySizeLabel
🏠 Remote policy remote	🏭 Industry companyIndustry, sectors companySectors
💲 Salary salaryMin, salaryMax, salaryCurrency, salaryPeriod	📅 Founded companyCreationYear
💲 Yearly salary floor salaryYearlyMin, hasSalary	💰 Revenue companyRevenue, turnover companyTurnover
🎓 Experience experienceMin, experienceLevelLabel, educationLevel	🔗 Social links companyLinkedin, companyTwitter, companyFacebook, companyInstagram, companyYoutube
🗂️ Profession professionName, professionCategoryName, professionSubCatName	📸 Logo companyLogoUrl, cover image companyCoverImageUrl
🏷️ Department department, sectors sectors	📝 Description companyDescription, summary companySummary
📍 Offices offices (city, country, address, coordinates)	📍 Headquarters companyHeadquarter
📅 Dates publishedAt, updatedAt, archivedAt	📊 Open jobs companyJobsCount, average age companyAverageAge
📝 Text summary, description, profile, keyMissions, team	⚖️ Parity companyParityMen, companyParityWomen, companyEqualityIndex
🧰 Skills skills, tools tools, benefits benefits	🏷️ Labels companyLabels
📋 Hiring steps recruitmentProcess, startDate, atsQuestions, applicationFields	🛠️ Hiring setup companyHasExternalAts, companyAutomaticEmail, companyGdprSetting
🆔 IDs id, objectId, reference, slug, status status	🆔 companyId, companySlug
🌐 language, websiteCountry, contractDurationMin, contractDurationMax, scrapedAt	🗂️ professionCategory, professionSubCat

Note: A value is null when the job site doesn't provide it. Salary fields are filled only when the employer discloses pay (hasSalary = true). The full listing text, skills, tools, benefits, apply link, id and most extended company fields need Include Full Job Details (includeDetails, on by default). objectId, contractTypeName, experienceMin, salaryYearlyMin, department, sectors and companySizeLabel come from the search and are null for direct job links. salaryYearlyMax is always null.

What data can't Welcome to the Jungle Jobs Scraper extract?

• Applicant or candidate data, and recruiters' personal contact details
• Jobs that are only visible after logging in (it collects public listings only)
• Company pages without a job link (paste job links, not company links)
• Articles and editorial content from the job site

If you need startup and company data with founders and open roles, try Y Combinator Scraper.

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🧭 How to scrape Welcome to the Jungle jobs

There's nothing to install: this Welcome to the Jungle extractor runs in the Apify cloud, and you control it from your browser. Here's how to extract Welcome to the Jungle jobs in five steps:

1. Create a free Apify account using your email.
2. Open Welcome to the Jungle Jobs Scraper.
3. Fill in the form. No field is required:
   • Type a Search Query, such as data analyst.
   • To get jobs in one country, pick it in Country Filter (for example FR for France), or type a city in Location.
   • Optionally pick a Contract Type (for example Full-time (permanent)) and a Remote Work Policy.
   • Leave Industry Sector and Job Category empty for your first run.
   • Already have job links? Paste them into Direct Job URLs instead.
4. Click Start and wait for the run to finish. Jobs appear in the dataset one by one as soon as each is ready.
5. Download your data in JSON, CSV, Excel, XML or HTML.

⚠️ Website Region is not a country filter. It only chooses which regional site (English, French, Spanish, Czech or Slovak) is used for the labels in your results (such as contract type, category, sector, skill and benefit names) and for the language part of the job and company URLs. It doesn't change which jobs the search finds, and job titles and descriptions stay in their original language. To filter by country, use Country Filter. If you set Website Region to French, Spanish, Czech or Slovak, also read Sector and job category keywords, because English Job Category keywords can then empty your results.

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💲 How much does it cost to scrape Welcome to the Jungle jobs?

Welcome to the Jungle Jobs Scraper uses pay-per-event pricing. Your bill has three parts:

1. Results: $3.00 per 1,000 results on the Free plan (lower on paid plans, see below), that is $0.003 for every job saved to the dataset.
2. Actor start: a small fee once per run, priced at $0.00005 per GB of run memory (at least $0.00005). At the default 1 GB of memory, that's $0.00005 per run.
3. Apify platform usage: the computing resources your run uses. It depends on the run (its memory and how long it runs), isn't included in the prices above, and you pay for it on top. After each run, you can see it on the run's detail page in Apify Console.

Apify plan	Price per job	Price per 1,000 jobs
🆓 Free	$0.003	$3.00
🌱 Starter	$0.0025	$2.50
📈 Scale	$0.002	$2.00
🏛️ Business and higher	$0.0015	$1.50

Paid Apify plans get a lower result price. The plan discount applies to the result price only. The start fee is the same on every plan, and platform usage is billed at your Apify plan's own rates.

Example costs (results only, Free plan prices):

• 100 jobs: 100 × $0.003 = $0.30
• 1,000 jobs: 1,000 × $0.003 = $3.00

Add $0.00005 for the start at default memory, plus platform usage. See the pricing tab for the current events.

Is scraping Welcome to the Jungle jobs free?

You can try it for free. The Apify Free plan includes $5 of monthly credit, and Free-plan runs work the same as paid runs. That credit is shared: it pays for this Actor's event charges (results and start) and for platform usage. Set a maximum charge limit when you start a run, and do a small test run first.

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⬇️ Welcome to the Jungle Jobs Scraper input

No input field is required. With an empty input, the Actor searches all jobs and saves up to 100 results (the Maximum Jobs to Scrape default). You can fill in the form in Apify Console or send the input as JSON through the API.

Here's an example that searches full-time data analyst jobs with an office in France and saves 10 jobs with full details:

{
    "query": "data analyst",
    "countryCode": "FR",
    "contractTypes": ["FULL_TIME"],
    "maxItems": 10,
    "includeDetails": true
}

See the input tab for every field.

Keyword search mode and direct-link mode

The WTTJ jobs scraper runs in one of two modes:

• Keyword search mode (default): Direct Job URLs is empty. The Actor runs a Welcome to the Jungle job search with your Search Query and filters.
• Direct-link mode: Direct Job URLs contains at least one link. The search and the search filters are skipped, and only those jobs are scraped, always with full details. Posted Within and Job Category are still checked (see below).

Main settings

Name in the form	Input name	What it does	Default
Direct Job URLs	startUrls	Job links to scrape; switches to direct-link mode	empty
Search Query	query	Job title, skill or company; empty = all jobs	empty
Match query in job title only	searchOnlyInJobTitle	Match the query in job titles only	off
Website Region	websiteCountry	Not a location filter. Chooses the regional site (en, fr, es, cs, sk) used for labels and URLs. To filter by country, use Country Filter	en
Location	location	City, region or country name to search around; worldwide = no location filter. Ignored when Country Filter is set	none
Search Radius (miles)	locationRadius	5, 10, 20, 50 or 100 miles around Location (1 mile ≈ 1.6 km, so 20 miles ≈ 32 km)	20
Country Filter	countryCode	ISO code of the job's office country (FR, DE, ES…)	none
Sort Results By	sortBy	Relevance or Newest first (date); see Sorting	relevance
Posted Within	datePosted	Any time, or the last 1, 3, 7, 14 or 30 days	any time
Contract Type	contractTypes	FULL_TIME, PART_TIME, INTERNSHIP, APPRENTICESHIP, FREELANCE, TEMPORARY, GRADUATE_PROGRAM, VIE, VOLUNTEER, OTHER	all
Remote Work Policy	remote	Fully remote (fulltime), Hybrid (partial), Occasional remote (punctual), On-site only (no), Unknown (unknown)	all
Industry Sector	sector	Industry keywords; keyword search mode only (see below)	all
Job Category	categories	Job category keywords (see below)	all
Experience Level, Min Experience (years), Max Experience (years)	experienceLevel, experienceMin, experienceMax	Years of experience required	none
Minimum Yearly Salary	salaryMin	Minimum disclosed yearly salary, in the job's currency	none
Company Size	companySize	0-15, 15-50, 50-250, 250-2000, 2000+ employees	none
Job Content Language	language	Language the job is written in (en, fr, de, es…)	all
Maximum Jobs to Scrape	maxItems	Most jobs to save in one run; 0 = no result limit	100
Include Full Job Details	includeDetails	Load the full listing for every job	on

Values inside one filter are combined with OR; different filters are combined with AND.

Advanced settings

You can usually leave these at their defaults.

Name in the form	Input name	What it does	Default
Proxy Configuration	proxyConfiguration	Optional Apify Proxy settings; custom proxy URLs aren't supported	no proxy
Concurrent Requests	concurrency	Job pages loaded at the same time (1–30)	8
Max Retries per Request	maxRetries	Attempts for a request that fails (1–5)	3
Delay Between Search Pages (seconds)	requestDelay	Pause between search requests in very large searches (0–10)	0

Direct job links (startUrls)

Paste links into Direct Job URLs when you already know which jobs you want.

• ✅ Good: https://www.welcometothejungle.com/en/companies/<company>/jobs/<job>
• ❌ Bad: https://www.welcometothejungle.com/en/companies/<company> (a company page, not a job link; it's skipped with a warning)

⚠️ With direct links, keep Posted Within on Any time. Any other value removes every direct link, because no posting date is known at that point. Keep Job Category empty, and set Maximum Jobs to Scrape to at least the number of links (or 0). Repeated links are not merged, so each copy is scraped and charged. If a link points to a removed job, or its listing can't be loaded, a near-empty record (with title and companyName set to null) is still saved and charged.

Location and countryCode

Country Filter (countryCode) overrides Location (location). The radius only applies when Location is set and Country Filter is empty. A location that can't be found is skipped, and the run continues without the radius filter.

• ✅ Good: "location": "Paris", "locationRadius": "20" or "countryCode": "FR"
• ❌ Bad: setting both location and countryCode and expecting the radius to apply

Sector and job category keywords

Industry Sector (sector) and Job Category (categories) take keywords such as tech, finance or marketing, not exact values. Each keyword is matched (case-insensitive, partial match) against the job site's current lists. A sector keyword is matched against the English sector names, whatever Website Region is set to, and works in keyword search mode only. A sector keyword that matches nothing is ignored with a warning.

With Include Full Job Details on (the default), each saved job must also match at least one Job Category keyword in its full listing. That double-check uses the category names in the Website Region language.

• ✅ Good: "categories": ["marketing"] with "websiteCountry": "en"
• ❌ Bad: "categories": ["sales"] with "websiteCountry": "fr" (an English keyword checked against French category names)

⚠️ With Website Region set to fr, es, cs or sk and full details on, English Job Category keywords can remove every job. Pick one fix: leave Website Region on en; type the keywords in that region's language; or, in keyword search mode, turn Include Full Job Details off (you then get the core search fields only). An unknown Job Category keyword can also reduce or empty your results.

Maximum Jobs to Scrape (maxItems)

Maximum Jobs to Scrape is the most jobs saved in one run. It's 100 by default. Set it to 0 for no result limit; very large searches (for example, all jobs with no filters) may not return every match, so narrow very broad searches with filters.

Sorting and the posted-date window

Sort Results By = Newest first (date) sorts the jobs the Actor has collected, newest first. It doesn't look for newer jobs: the Actor first collects up to Maximum Jobs to Scrape matching jobs in relevance order, then sorts that set. If your search has more matches than that, the newest jobs may not be among them. To be sure recent jobs are included, narrow the search with filters or raise Maximum Jobs to Scrape (or set 0), then use Posted Within (for example Last 7 days) to keep only recent jobs. Jobs are saved as each one finishes, so sort by publishedAt in your spreadsheet if you need strict date order.

Posted Within and the Job Category double-check run after the matching jobs are collected, so a run can save fewer jobs than Maximum Jobs to Scrape.

Minimum salary (salaryMin)

Only listings that publish a yearly salary can match, so Minimum Yearly Salary excludes jobs without disclosed pay. The value is in the job's local currency.

• ✅ Good: "salaryMin": 50000

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⬆️ Welcome to the Jungle Jobs Scraper output

Results are stored in a dataset in the Output or Storage tab. You can view them as a table or as JSON, pick only the fields you need, and download them in JSON, CSV, Excel, XML or HTML. To export jobs to CSV with every field, use the CSV Export link in the Output tab or the dataset's export button. All saved jobs are also stored as one JSON file in the run's key-value store under the OUTPUT key.

The dataset has four ready-made views:

• Overview: logo, title, company, contract type, remote policy, salary, posting date and URL
• Compensation & Experience: salary fields, experience, education and company size
• Company Profile: industry, size, founding year, revenue, website, LinkedIn page and open jobs
• Full Listing: summary, description, candidate profile, benefits, skills, tools, apply link and recruitment process

Opening the data in Excel or CSV

Each job has 80 fields. In a CSV or Excel export, list and nested fields such as offices, skills, tools and companyHeadquarter are spread across several columns (for example, one set of columns per office), so a full export has more than 80 columns. For a lighter spreadsheet, start from the Overview view, or pick only the fields you need before you export.

JSON example

Results for the input example above. This record is shortened and its values are illustrative only (the company is fictional); a real record always has all 80 fields.

[
    {
        "id": "EXAMPLE-ID",
        "reference": "EXAMPLE-REF",
        "slug": "data-analyst_paris",
        "title": "Data Analyst",
        "url": "https://www.welcometothejungle.com/en/companies/example-company/jobs/data-analyst_paris",
        "applyUrl": "https://careers.example.com/data-analyst",
        "language": "fr",
        "websiteCountry": "en",
        "contractType": "FULL_TIME",
        "remote": "partial",
        "experienceMin": 3,
        "salaryMin": 45000,
        "salaryMax": 55000,
        "salaryYearlyMin": 45000,
        "salaryCurrency": "EUR",
        "hasSalary": true,
        "professionName": "Data Analyst",
        "publishedAt": "2026-10-01T09:00:00Z",
        "offices": [
            {
                "city": "Paris",
                "country": "France",
                "countryCode": "FR",
                "zipCode": "75001"
            }
        ],
        "summary": "Join our data team to build dashboards and…",
        "skills": [{ "name": "SQL", "reference": "example-skill" }],
        "tools": [{ "name": "Tableau", "reference": "example-tool" }],
        "benefits": ["Remote work", "Meal vouchers"],
        "companyName": "Example Company",
        "companySlug": "example-company",
        "companyUrl": "https://www.welcometothejungle.com/en/companies/example-company",
        "companySize": 120,
        "companyWebsite": "https://www.example.com",
        "companyCreationYear": 2015,
        "scrapedAt": "2026-10-08T10:00:00.000Z"
    }
]

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💡 Tips and advanced usage

How many results can you scrape with Welcome to the Jungle Jobs Scraper?

Maximum Jobs to Scrape is 100 by default, and 0 means no result limit, though very large searches may not return every match. The exact number also depends on how many jobs match your search and filters, the posted-date window, the Job Category double-check, Minimum Yearly Salary (jobs without disclosed pay are excluded) and your run's spending limit. The best way to know is a quick test run.

How to get faster or cheaper results

• Turn Include Full Job Details off when you only need the core search fields. The run is faster, but fields such as the description, apply link, skills and extended company profile stay null.
• Narrow the search with filters (Country Filter, Contract Type, Remote Work Policy, Posted Within) so you only pay for the jobs you need.
• Set Maximum Jobs to Scrape to the number of jobs you really need.
• Set a spending limit on your run. The Actor respects it and stops cleanly; jobs saved before the stop stay in the dataset.

Run it on a schedule: a daily feed of new jobs

To follow new WTTJ job listings for a role or market every day:

1. Set your search, for example Search Query data analyst, Country Filter FR, Contract Type Full-time (permanent), Posted Within Last 24 hours and Maximum Jobs to Scrape 0 (no result limit), so the newest jobs aren't cut off by the limit.
2. Save the input as a task in Apify Console, so every run uses the same search.
3. Open the task, choose Schedule, and add an Apify schedule that runs it once a day.
4. Compare runs: duplicates are removed within a run only, so merge the daily datasets on url (or id) to drop repeats. Then count jobs per companyName, professionName or contractType per week to see who is hiring more, or track salaryMin by role over time.

Use a weekly schedule with Posted Within Last 7 days if you only need a weekly report.

Known issues

• If a job's full listing can't be loaded, the job is still saved with its basic fields only. Because the Job Category double-check needs the full listing, such a job is kept even if it doesn't match your Job Category keywords, so an occasional off-category job can appear.
• Duplicate jobs from a keyword search are removed, but repeated direct links are not.
• salaryYearlyMax is always null, because only a yearly salary floor is published.
• Custom proxy URLs (your own proxies) aren't supported and are ignored. The Actor can use Apify Proxy.

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🔌 Welcome to the Jungle Jobs Scraper integrations and API

Can I use Welcome to the Jungle Jobs Scraper as an API?

Yes, through the Apify API. This is not an official Welcome to the Jungle API or WTTJ API: you use the Apify API for this Actor to start runs, schedule them and fetch the results programmatically, so you can call it as a Welcome to the Jungle jobs API from your ATS, CRM or app. Use the apify-client NPM package for Node.js or the apify-client PyPI package for Python. The API tab has ready-to-use code.

How to scrape WTTJ jobs with Python

Here's a short job scraper Python example using the Apify client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("insights_data/welcome-to-the-jungle-jobs-scraper").call(run_input={
    "query": "data analyst",
    "countryCode": "FR",
    "contractTypes": ["FULL_TIME"],
    "maxItems": 10,
    "includeDetails": True,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], item["companyName"], item["url"])

The same calls work from any language that can send HTTP requests, so the Actor can serve as the job listings API behind your own job board or app.

Can I integrate Welcome to the Jungle Jobs Scraper with other apps?

Yes. Connect it with almost any cloud service through Apify integrations: Make, Zapier, Slack, Google Sheets, Google Drive, Airbyte, GitHub, LangChain and more. Use webhooks to act whenever a run finishes.

Example workflows:

• Google Sheets and Slack for recruiters: schedule the daily task from the tip above, add the Google Sheets integration so each run adds the new jobs to a sheet, and the Slack integration so your recruiting team gets a message with the run link.
• Job board feed through Make or Zapier: a webhook on the "run succeeded" event starts a Make scenario or a Zap that reads the run's dataset and creates one item per job (title, company, contract type, remote policy, salary, apply link) in Airtable, Webflow or your own job board.
• Lead list for sales: a weekly run on your target market sends companyName, companyWebsite, companyLinkedin, companySize and companyIndustry to your CRM through Zapier, so sales teams see which companies are hiring.

Can I use Welcome to the Jungle Jobs Scraper with AI agents (MCP)?

Yes. Connect it to Claude and other AI assistants through the Apify MCP server, so an agent can search WTTJ jobs for you. Open the MCP tab for the setup steps.

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🔗 Other job and company data scrapers

These Actors from the same developer pair well with your Welcome to the Jungle job postings for recruiting and research:

💼 Advanced LinkedIn Job Search API	Scrape public LinkedIn jobs by search URL, job URL or title + location. Get title, company, salary, seniority, applicants and the full description as clean JSON, with no login or cookies.
🚀 Y Combinator Scraper	Extract Y Combinator company profiles, founders, open roles, press and Launch YC posts, filtered by batch. Built for lead gen, recruiting and deal sourcing.
👤 LinkedIn Profile Extractor & Enricher (No Login Required)	Extract public LinkedIn profiles from URLs or IDs without login: name, headline, location, current role, experience, education and skills as clean JSON.

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❓ FAQ

Is it legal to scrape job postings from the Welcome to the Jungle job site?

Scraping publicly available job postings is generally legal, but how you use the data matters. Job listings can include personal data (for example, a recruiter's name), so respect privacy rules such as the GDPR and only keep personal data when you have a legitimate reason. Also respect the job site's terms of service and the copyright of the listing text. This is not legal advice; read Is web scraping legal? on the Apify blog and ask a lawyer if you're unsure.

How does the Welcome to the Jungle jobs crawler work?

It works like a person using the Welcome to the Jungle job search, only faster. It runs your keyword search with the filters you choose (or takes the job links you paste) and collects the matching jobs up to your limit. With full details on, it then opens each job's full listing to add the description, apply link, skills, tools, benefits and company details. Every job is saved to your dataset as soon as it's ready, so a stopped run keeps what was already saved.

How to scrape job postings without coding?

Open the Actor, type a Search Query, pick your filters and click Start. When the run finishes, download the data as CSV or Excel, or connect a Google Sheet. You don't need to write code, manage servers or log in to the job site, and unlike a script-based job posting scraper, there's nothing to install or keep up to date. If you want to scrape job postings on a regular basis, add a schedule in Apify Console. Developers can also call it as a job scraper API (see the integrations and API section).

Why scrape Welcome to the Jungle job data?

• Salary benchmarking: compare disclosed salaries across roles, cities and company sizes.
• Job market data for research: count open roles by category, sector, contract type and remote policy.
• Recruitment data for talent teams: see which companies hire for the profiles you place.
• Job aggregator content: keep a niche job board filled with current WTTJ job listings and apply links.
• Remote job boards: run it as a remote jobs scraper with Remote Work Policy set to Fully remote or Hybrid.
• Sales prospecting: use hiring activity and Welcome to the Jungle company data (website, size, industry) as buying signals.

Can it collect Welcome to the Jungle remote jobs?

Yes. Use the Remote Work Policy filter (remote): Fully remote (fulltime), Hybrid (partial), Occasional remote (punctual) or On-site only (no). Every record also has the remote field, so you can filter after export too.

Can I collect only internships or apprenticeships?

Yes. Set Contract Type (contractTypes) to Internship, Apprenticeship / Work-study or Graduate program to collect early-career roles only. The same filter covers freelance, part-time, temporary, VIE and volunteer roles.

Does it scrape other job sites?

No. It isn't a general job board scraper: it covers only the Welcome to the Jungle job board (with labels and URLs in English, French, Spanish, Czech or Slovak). Unlike a generic job scraper, it returns the site's own fields, such as remote policy, profession category, benefits and company parity data. For LinkedIn job postings, use Advanced LinkedIn Job Search API and merge the outputs on the job title, company name and job link.

Can I scrape a list of specific job links?

Yes. Paste the links into Direct Job URLs (startUrls) to switch to direct-link mode. Keep Posted Within on Any time and Job Category empty, as explained in the input section.

Why am I getting fewer results than expected?

• Posted Within: it's applied after jobs are collected, so it can cut the result count. Widen it or use Any time.
• Job Category keywords: an unknown keyword, or English keywords with a non-English Website Region, can remove jobs. Use Website Region en or keywords in the region's language.
• Salary filter: Minimum Yearly Salary drops every job without a disclosed salary.
• Direct links: any Posted Within value other than Any time removes them; links that aren't job links are skipped.
• Location: a location that can't be found is skipped, and the radius filter isn't applied.
• Spending limit: the run stops when your spending limit is reached.

What should I do if my run fails or saves nothing?

1. Open the run in Apify Console and read its status message and Log tab. A finished run shows how many jobs were saved, and the log ends with a summary: jobs saved, jobs that couldn't be processed, and whether your spending limit stopped the run.
2. If no job matched, the log says so and suggests widening your filters. If none of your direct links is a job link, the log says there's nothing to do.
3. Jobs saved before a run stops stay in the dataset. Result charges apply only to jobs that were saved (plus the start event and platform usage).
4. Still stuck? Open an issue on the Issues tab with your input and a link to the run.

Who uses Welcome to the Jungle job listings data?

Recruiters and talent teams, HR and compensation analysts, job-board and job aggregator builders, market researchers and sales teams. It suits anyone who needs regular job data extraction but doesn't want to build and maintain their own WTTJ scraper.

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📧 Support and feedback

Found a bug or have a feature request? Please create an issue on the Issues tab.

Need a custom solution, extra fields or a scraper for another job site? Contact us at hello.insights.data@gmail.com.

Built and maintained by insights_data.