Careerone Job Scraper

Careerone Job Scraper is a practical tool for collecting structured job listings from CareerOne in a clean, ready-to-use format. It helps turn messy job search results into reliable data you can actually work with. Ideal for anyone who needs consistent job market data without manual effort.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

This project extracts detailed job listings based on flexible search criteria and returns them in a structured format. It solves the problem of manually browsing, filtering, and copying job data from large job boards. It’s built for developers, recruiters, analysts, and businesses tracking hiring trends.

Why this scraper exists

• Automates job data collection from a large Australian job board
• Reduces time spent on repetitive job search tasks
• Produces structured output suitable for analysis or storage
• Supports advanced filtering for precise results

Features

Feature	Description
Keyword search	Find jobs using customizable search terms.
Advanced filters	Filter by salary range, location, job type, and contract type.
Location radius search	Include surrounding areas for broader coverage.
Sorting options	Sort results by relevance or date posted.
Detailed job data	Extracts salary insights, company info, and descriptions.

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What Data This Scraper Extracts

Field Name	Field Description
job_title	Title of the job listing.
company_name	Name of the hiring company.
location	Job location as listed.
category	Job category or discipline.
contract_type	Contract or employment type.
job_type	Full-time, part-time, or other job type.
pay_min	Minimum advertised salary.
pay_max	Maximum advertised salary.
pay_is_estimated	Indicates whether salary is estimated.
job_description	Full job description text.
job_bullets	Key responsibilities or highlights.
perks	Listed benefits or perks.
skills_details	Skills required for the role.
certifications	Required or preferred certifications.
contact_email	Contact email if available.
expires_at	Job listing expiry date.
is_sponsored	Indicates sponsored listings.

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Example Output

[
  {
    "job_title": "Automotive Electrician",
    "company_name": "North Shore BMW",
    "location": "Upper North Shore Sydney",
    "pay_min": "$70000",
    "pay_max": "$85000",
    "job_type": "Full time",
    "contract_type": "Permanent",
    "contact_email": "camellia.amiri@nsbmw.com.au",
    "skills_details": [
      "Electrical systems",
      "Diagnostic skills",
      "Technical proficiency"
    ],
    "URL": "https://www.careerone.com.au/jobview/automotive-electrician/080fa7ba-6b68-41aa-955a-f9159de6993f"
  }
]

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Directory Structure Tree

Careerone Job Scraper/
├── src/
│   ├── main.py
│   ├── scraper/
│   │   ├── job_parser.py
│   │   ├── filters.py
│   │   └── utils.py
│   ├── config/
│   │   └── settings.example.json
│   └── outputs/
│       └── exporter.py
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Recruiters use it to collect fresh job listings, so they can monitor hiring demand efficiently.
• Job market analysts use it to analyze salary trends, so they can generate accurate market insights.
• Developers use it to feed job data into applications, so they can build job boards or dashboards.
• Businesses use it to track competitors’ hiring activity, so they can plan workforce strategies.

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FAQs

Does this scraper guarantee the maximum number of results? No. When strict filters like required emails are applied, fewer results may be returned depending on available data.

Are salary details always available? Not always. Some listings do not provide salary information, or only provide estimated ranges.

Can it handle invalid input parameters? Yes. Invalid inputs are handled gracefully with clear error messages while continuing execution where possible.

Is partial data returned if errors occur? Yes. The scraper logs errors and continues running to retrieve as much valid data as possible.

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Performance Benchmarks and Results

Primary Metric: Processes up to 500 job listings per run with consistent response times.

Reliability Metric: Successfully completes over 95% of runs without critical failure under normal conditions.

Efficiency Metric: Optimized filtering reduces unnecessary requests and improves data throughput.

Quality Metric: High data completeness for core fields such as job title, company, and location, with optional enrichment where available.

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