Job Listings jobs2careers Scraper | Fast Multi-Keyword Job Data Extractor

Extract structured job listings at scale from "https://www.jobs2careers.com/" using fast, asynchronous scraping with pagination, retries, and concurrency control.

This actor is designed for job market intelligence, recruitment automation, salary tracking, and workforce analytics.

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Performance Overview:

This run demonstrates the actor’s production-grade efficiency, processing 6,323 job listings in under a minute with low memory usage (~110 MB avg) and stable CPU utilization, confirming strong scalability and I/O-optimized architecture.

Overview

The Job Listings jobs2careers Scraper is a production-grade Apify actor that collects job advertisements based on keywords and locations.

It supports:

• Multi-keyword scraping
• Pagination handling
• Retry + rate-limit management
• Concurrent execution
• Structured job extraction

The scraper is optimized for:

• Job market analysis
• Talent intelligence
• Recruitment automation
• Remote job tracking
• Salary research datasets

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Key Features

• ⚡ Async concurrent keyword scraping
• 🔁 Automatic pagination support
• 🛡 Retry mechanism with exponential backoff
• 📦 Batch dataset output (optimized writes)
• 🎯 Multi-keyword input support
• 🌍 Location-based job filtering
• 📊 Scalable for large job datasets
• ⚙️ Apify-native architecture

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How It Works

1. Input keywords are parsed (comma-separated list)
2. Each keyword is processed concurrently (controlled with semaphore)
3. The scraper queries job search endpoints using structured parameters
4. Results are paginated automatically
5. Job ads are normalized and stored in Apify dataset
6. Retry logic handles rate limits and server errors

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Input Configuration

Required Fields

Field	Type	Description
keywords	string	Comma-separated list of job search keywords
location	string	Job location (e.g., "New York, NY")

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Optional Fields

Field	Type	Description
maxItems	integer	Maximum number of job ads to scrape per keyword
benefit	string	Filter by job benefits
workType	string	Full-time / Part-time / Contract
date	string	Date filter (e.g., last 24h, last 7d)
salary_period	string	Salary time unit
commute	integer	Commute distance filter

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Example Input

{
  "keywords": "data engineer, data scientist, backend developer",
  "location": "New York, NY",
  "maxItems": 500,
  "workType": "full-time"
}

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Output Data Structure

Each job listing is stored as a structured JSON object:

{
  "id": "35892049874",
  "title": "Field Structural Engineer (Solar Focused)",
  "companyName": "Pure Power Engineering",
  "location": "Hoboken, NJ",
  "datePosted": "2026-05-22T16:01:39Z",
  "url": "https://www.jobs2careers.com/click.php?jid=8d6832031b0d71e28f5afe9e7&ri=a1db1e549b954c1fa3ef3b05637f2a27&job_loc=Hoboken%2CNJ&q=Software+Engineer&spl=v1%253AV9wSHugKYWd9KGZD%253A8TXGhxAQtDPG9fqH5TYPJw%253D%253D%253A18dS4pTsadmGGlLVb5OLOficnbhE7zcyMSOdLATNAYQheBoVGGEKbm9tA2cIjZ3c5r3ensThSV0aB6MjmONK6CHeE%252FQHgHWeWe5DccHn2GXPWLMalGu2bph5cT2YTXxU78E%252BuAJGE7%252BTsrOCi2YGaMy1nXHBG8La0%252FJVxJA%252F&encrypt=0&l=New+York%2C+NY&query_category_id=400000",
  "description": "Description:<p> </p><p>Pure Power Engineering is seeking a Field Structural Engineer with extensive on-site experience to support our rapidly growing solar engineering portfolio. This role is ideal for a hands-on engineer who excels at evaluating existing structures in the field, understanding a wid",
  "salary": {},
  "benefits": [
    "Health Insurance",
    "Retirement Benefit"
  ],
  "workType": "Full Time",
  "workLocation": "hybrid",
  "category": {
    "major": "Engineering",
    "minor": "Engineering Electrical Engineer"
  },
  "techCategory": {
    "major": "Construction",
    "minor": "Construction Civil Engineer"
  },
  "requirements": [],
  "applyType": "Easy Apply",
  "coordinates": {
    "lat": 40.737377,
    "lng": -74.028305
  },
  "companyLogo": "https://media.j2c.com/company-logos/1927659-pure_power_engineering-e4d194f0",
  "relevanceScore": 0.994941
}

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Use Cases

📊 Job Market Intelligence

Analyze demand trends across job categories and locations.

🧠 Salary Research

Build datasets for compensation benchmarking.

🏢 Recruitment Automation

Feed structured job data into ATS or CRM systems.

🌍 Remote Work Tracking

Monitor remote job availability globally.

📈 Workforce Analytics

Study hiring trends across industries and skills.

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Performance & Scalability

• Concurrent keyword processing (Semaphore controlled)
• Async HTTP request handling
• Exponential retry backoff for stability
• Batched dataset writes (optimized I/O)
• Pagination-aware scraping engine

Designed for medium-to-large scale job data extraction.

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Architecture

Concurrency Model

• Multiple keywords processed in parallel
• Controlled concurrency via semaphore
• Sequential pagination per keyword (safe against rate limits)

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Reliability Features

• Automatic retry on:
  • 429 (rate limit)
  • 403 (blocked requests)
  • 5xx server errors
• Exponential backoff strategy
• Graceful failure handling per keyword
• Partial success support (non-blocking execution)

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Best Practices

• Use 2–5 keywords per run for optimal performance
• Use realistic location filters
• Schedule periodic runs for monitoring use cases

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SEO Keywords

Job scraper, job listings scraper, job API scraper, job data extractor, job market dataset, recruitment scraper, remote job scraper, salary data scraper, hiring trends scraper, workforce analytics scraper.

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Common Users

• Recruiters
• HR tech companies
• Data analysts
• AI dataset builders
• Job board aggregators
• Market research firms

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Support

This actor is actively maintained and designed for production scraping workflows on Apify.

For issues or improvements, use the Apify platform issue tracker.