Working Nomads Jobs Scraper

Working Nomads Jobs Scraper — Collect Remote Job Listings

Overview

Working Nomads Jobs Scraper collects publicly available remote job listings and saves matching opportunities as structured dataset rows. Filter jobs by keyword or category, limit the number of results, and export the collected data in JSON, CSV, or Excel format.

The scraper helps organize remote job opportunities by title, company, category, tags, location, and publication date.

Features

• Keyword filtering: Find jobs by matching keywords in job titles and tags.
• Category filtering: Narrow results to categories such as Development or Marketing.
• Custom result limits: Choose how many matching jobs to collect, up to 1,000 per run.
• Duplicate removal: Avoid saving multiple records with the same job listing URL.
• Clean descriptions: Remove HTML markup from job descriptions.
• Structured datasets: Save job information in clearly named fields.
• Multiple export formats: Work with JSON, CSV, or Excel files.

Use Cases

• Remote job boards: Build categorized lists of remote opportunities in specific fields.
• Recruiting research: Organize company names, job categories, skills, and publication dates.
• Keyword monitoring: Collect roles mentioning technologies such as Node.js, Python, or JavaScript.
• Category-based research: Focus on Development, Marketing, or other available categories.
• Scheduled job collection: Maintain recurring snapshots of remote job listings.
• Job market analysis: Compare job titles, company information, required skills, and publication dates.

Input Parameters

Parameter	Type	Default	Description
keyword	String	Empty	Case-insensitive keyword filter applied to job titles and tags.
category	String	Empty	Case-insensitive filter applied to the job category name.
maxItems	Integer	100	Maximum number of matching jobs to save. The allowed range is 1–1,000.
timeoutSecs	Integer	300	Overall run time limit in seconds. The allowed range is 1–3,600.
requestTimeoutSecs	Integer	30	Maximum wait for the job feed request, in seconds. The allowed range is 1–300.

Example Input

{
  "keyword": "nodejs",
  "category": "Development",
  "maxItems": 100,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30
}

This example collects up to 100 matching jobs in the Development category whose titles or tags contain nodejs.

What Data Does This Actor Extract?

Each collected job is saved as one dataset row. Job descriptions are converted to plain text, and duplicate job listing URLs are removed.

The title and description values are stored as jobTitle and jobDescription to maintain a compatible dataset schema.

Extracted Data Fields

Field	Type	Description
url	String	Link to the individual job listing.
jobTitle	String	Job title in plain text.
jobDescription	String	Job description with HTML markup removed.
company_name	String	Name of the hiring company.
category_name	String	Category assigned to the job.
tags	String	Comma-separated tags associated with the job.
location	String	Job location or time-zone information.
pub_date	String	Job publication timestamp supplied by the feed.
scrapedAt	String	UTC timestamp indicating when the record was saved.

Example Output

{
  "url": "JOB_LISTING_URL",
  "jobTitle": "Senior Backend Developer (Node.js / Nest.js)",
  "jobDescription": "About us: Talent has no borders.",
  "company_name": "Proxify",
  "category_name": "Development",
  "tags": "back-end,nodejs,typescript,javascript,graphql",
  "location": "Time zone: CET (+/- 3 hours)",
  "pub_date": "2026-10-08T12:54:14-04:00",
  "scrapedAt": "2026-10-12T00:00:00+00:00"
}

The example illustrates the dataset structure. Actual values depend on the available job listings and the time of collection.

Working with Your Dataset

After the run completes, use the dataset to:

• Export job records to JSON, CSV, or Excel.
• Filter and sort opportunities by category, company, or publication date.
• Search tags to identify roles requiring particular technologies.
• Import the results into spreadsheets or your own job-tracking workflow.
• Compare job listings across different collection runs.

Important Notes

• Keyword and category filters are case-insensitive.
• Keyword matching checks job titles and tags; it does not search the entire job description.
• Category matching uses the category name.
• Duplicate job listing URLs are removed.
• The maximum number of saved matching jobs is 1,000 per run.
• The result limit is applied after the job feed is retrieved and filtered.
• If no jobs match the filters, the actor may finish without producing job records.
• Job availability and listing details can change between runs.

FAQ

How many jobs can I collect in one run?

The default limit is 100 jobs. You can increase it to a maximum of 1,000 using maxItems.

Can I filter jobs by technology?

Yes. Enter a technology or skill in keyword. The scraper checks job titles and tags for case-insensitive matches.

Can I collect only Development jobs?

Yes. Set category to Development, or specify another category available in the feed.

Are job descriptions saved as HTML?

No. HTML markup is removed, and the description is saved as plain text in jobDescription.

Why is the title field named jobTitle?

The actor uses jobTitle and jobDescription to maintain a compatible dataset schema.

What happens when multiple records contain the same job listing URL?

Duplicate job URLs are discarded so the dataset does not contain repeated listings with the same URL.

Which export formats are supported?

The dataset can be exported in JSON, CSV, and Excel formats.

Will every run return the same jobs?

Not necessarily. Available listings and their details can change over time. The results also depend on your filters and item limit.

Disclaimer

This is an independent tool and is not affiliated with, endorsed by, sponsored by, or officially associated with Working Nomads or its owners. The scraper is intended to help users organize publicly available job information. Users are responsible for ensuring that their collection, storage, and use of the data comply with applicable laws and the relevant website's terms.

Is Web Scraping Legal?

Collecting information that is already public is generally legal. Scraping is not the same thing as hacking, and there is no single law that bans it. The limits are the usual ones: do not break into accounts, do not take private or confidential data, and be careful with personal data and copyrighted works. A site's terms can also restrict how you access it. Facts such as a public name, price, or rating are not the same thing as republishing someone's article or photo.

This actor collects information from public pages. It does not log in and it does not bypass access controls.

For a longer explanation, see Apify's article Is web scraping legal?.