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Startup Jobs Scraper

The Startup Jobs Scraper extracts job listings from startupjobs.cz — gathering job titles, company names, locations, descriptions, and more. It’s ideal for recruiters, analysts, or anyone looking to build job-market datasets or monitor startup hiring trends. The scraper outputs clean, structured data that can be used in dashboards, CRMs, or analysis workflows.

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Introduction

Finding and tracking startup job openings manually can be tedious and error-prone. This scraper automates that work by crawling startupjobs.cz, collecting all relevant data points, and delivering them as a structured dataset — saving time and ensuring consistency.
Whether you want to build a job board, aggregate hiring data, or run market analysis, this tool gives you a solid foundation.

Why It Matters

  • Automatically aggregates fresh job listings from a startup-focused job board.
  • Allows filtering by employment type, location, seniority, salary, and more.
  • Produces structured output ready for downstream consumption (CSV, JSON, database, etc.).
  • Simplifies building analytics or lead-generation workflows based on hiring data.

Features

Feature Description
Job Listing Extraction Scrapes job title, company name, location, description, and full listing link. :contentReference[oaicite:0]{index=0}
Filter Support Supports input filters like employment type, location, seniority, cooperation type, job area, and salary constraints. :contentReference[oaicite:1]{index=1}
Structured Output Returns clean JSON output, exportable to CSV, Excel or database integration. :contentReference[oaicite:2]{index=2}
Configurable Job Count Allows specifying number of job ads to fetch (default is 40, minimum 20). :contentReference[oaicite:3]{index=3}
Proxy & Anti-blocking Utilizes crawling library with proxy/support to mitigate blocking and ensure stable results. :contentReference[oaicite:4]{index=4}
Multi-format Access Can be used via Apify UI, API (Python/JS/CLI), or CLI for flexible integration. :contentReference[oaicite:5]{index=5}

What Data This Scraper Extracts

Field Name Field Description
jobTitle Title of the job position.
companyName Name of the hiring company.
location Location or work-arrangement (remote, hybrid, city, etc.).
description Full job description and requirements.
employmentType Type of employment (full-time, part-time, contract, freelance, etc.) — if available. :contentReference[oaicite:6]{index=6}
seniorityLevel Seniority filter (e.g. junior, medior, senior) — if used in input filters. :contentReference[oaicite:7]{index=7}
jobAreas Job area tags (e.g. backend, marketing, sales) when listed. :contentReference[oaicite:8]{index=8}
salary Salary information (currency, salary type, minimum salary filter) — if available/applicable. :contentReference[oaicite:9]{index=9}
listingUrl Direct URL to the job posting.
companyLogo URL to the company’s logo image (if provided).

Example Output

[
  {
    "jobTitle": "Frontend Developer",
    "companyName": "Tech Startup A",
    "location": "Prague, Czechia (Remote possible)",
    "description": "We are looking for a motivated frontend developer to join our rapidly growing team...",
    "employmentType": "Full-time",
    "seniorityLevel": "Junior/Medior",
    "jobAreas": ["Front-end", "Web Development"],
    "salary": {
      "currency": "CZK",
      "type": "monthly",
      "min": 60000
    },
    "listingUrl": "https://startupjobs.cz/jobs/12345",
    "companyLogo": "https://cdn.startupjobs.cz/logos/tech-startup-a.png"
  }
]

Directory Structure Tree

startup-jobs-scraper/
├── src/
│   ├── main.js
│   ├── crawler/
│   │   ├── request_handler.js
│   │   ├── filter_parser.js
│   │   └── listing_extractor.js
│   ├── utils/
│   │   ├── proxy_manager.js
│   │   ├── logger.js
│   │   └── data_cleaner.js
│   └── config/
│       └── input_schema.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── package.json
└── README.md

Use Cases

  • Recruiters build curated startup-job databases for candidate sourcing or outreach.
  • Job boards or aggregators automatically fetch and refresh listings without manual curation.
  • Market researchers analyze hiring trends, tech demand, salary ranges, and job market shifts.
  • Freelancers / remote workers monitor job openings across startup-oriented markets.
  • Data analysts / HR teams integrate job data into dashboards, reporting tools or CRM systems.

FAQs

Which sites does this scraper support?
This scraper targets startupjobs.cz — it may not work properly for other job portals without modification. :contentReference[oaicite:10]{index=10}

Can I filter by job type, seniority, or salary?
Yes — input parameters allow filtering jobs by employment type, seniority, location, job area, salary currency and more. :contentReference[oaicite:11]{index=11}

What output format do I get?
The scraper outputs structured JSON. You can export or convert it to CSV, Excel, or use it for database import. :contentReference[oaicite:12]{index=12}

Does it handle big batches of jobs?
Yes — you can set the numAds parameter to fetch larger batches (minimum 20, default 40). :contentReference[oaicite:13]{index=13}

How can I integrate it into my workflow?
You can run it via the Apify platform UI, or programmatically via its API (Python, JS, CLI), then process the dataset results. :contentReference[oaicite:14]{index=14}


Performance Benchmarks and Results

Primary Metric:
Able to scrape 40–100 job listings within a few seconds or minutes depending on filters and proxy settings.

Reliability Metric:
Reported run success rate over 96% across recent runs. :contentReference[oaicite:15]{index=15}

Efficiency Metric:
Rate limiting and proxy rotation minimize blocking risks while maintaining throughput. :contentReference[oaicite:16]{index=16}

Quality Metric:
Provides full job metadata including location, company, description, and relevant tags — suitable for analytics, dashboards, or job-market studies. :contentReference[oaicite:17]{index=17}


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