Startup Jobs Scraper

Extract startup job listings from Startup.jobs for hiring research, compensation analysis, and market monitoring. Collect structured job data including titles, companies, locations, salary ranges, posting dates, logos, tags, role IDs, and job links in a fast automated run.

Features

• Startup Job Collection - Gather remote and startup job records with core hiring details.
• Keyword And Location Filters - Target roles, skills, remote jobs, or custom Startup.jobs listing URLs.
• Rich Listing Records - Capture salary, location, company, role, posting date, and geo fields when available.
• Clean Dataset Output - Duplicate jobs are skipped and empty values are removed from records.
• Fast QA-Friendly Runs - Start with 20 results and increase volume after confirming the output.

Use Cases

Talent Intelligence

Track hiring demand across startup roles, company types, and experience levels. Build repeatable datasets for recruiting strategy, workforce planning, and market snapshots.

Recruitment Operations

Collect fresh job openings for sourcing workflows, job alerts, or internal research dashboards. Use keyword and location filters to focus on the roles your team cares about.

Compensation Research

Analyze published salary ranges by role, company, location, and seniority. Combine salary_min, salary_max, and salary_currency fields with posting dates to monitor pay trends.

Market Research

Study startup hiring patterns, role requirements, company activity, and remote work availability. Export results to spreadsheets or BI tools for further analysis.

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Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	No	-	Custom Startup.jobs listing URL. When provided, it overrides keyword and location filters.
keyword	String	No	""	Job title, skill, or search phrase to target.
location	String	No	"Remote"	Location filter. Use Remote for remote-first collection.
results_wanted	Integer	No	20	Maximum number of jobs to collect, from 1 to 500.
max_pages	Integer	No	3	Maximum number of result pages to process, from 1 to 20.

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Output Data

Each dataset item can contain:

Field	Type	Description
id	String	Unique job identifier.
title	String	Job title.
company	String	Hiring company name.
location	String	Job location or remote status.
job_type	String	Human-readable employment type.
salary	String	Human-readable salary range when published.
posted_at	String	Job publish timestamp.
company_logo	String	Company logo URL.
apply_link	String	Application or job destination link.
url	String	Startup.jobs listing URL.
source	String	Source label for listing records.
fetched_at	String	Collection timestamp in ISO format.
tags	Array	Role, function, or topic tags.
workplace_type	String	Workplace model, such as remote.
employment_type	String	Published employment type code.
experience_bucket	String	Experience level category when provided.
salary_min	Number	Minimum salary value when published.
salary_max	Number	Maximum salary value when published.
salary_currency	String	Salary currency code.
city	String	City when provided.
country	String	Country when provided.
country_code	String	Country code when provided.
country_id	Number	Startup.jobs country identifier.
city_id	Number	Startup.jobs city identifier.
state_id	Number	Startup.jobs state identifier.
company_id	Number	Startup.jobs company identifier.
company_slug	String	Company slug identifier.
role_ids	Array	Role category IDs associated with the job.
location_parts	Array	Structured location parts.
published_at_unix	Number	Publish timestamp as Unix seconds.
created_at_unix	Number	Creation timestamp as Unix seconds.
has_salary	Boolean	Whether a salary range is published.
salary_interval	String	Salary period, such as year.
salary_min_usd	Number	Minimum salary converted to USD when available.
salary_max_usd	Number	Maximum salary converted to USD when available.
geo_lat	Number	Latitude when provided.
geo_lng	Number	Longitude when provided.
highlighted	Boolean	Whether the listing is highlighted.
missing_fields	Array	Core fields unavailable for that record, only included when needed.

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Usage Examples

Basic Remote Collection

{
    "location": "Remote",
    "results_wanted": 20
}

Keyword-Focused Search

{
    "keyword": "software engineer",
    "location": "Remote",
    "results_wanted": 50,
    "max_pages": 5
}

Custom Listing URL

{
    "startUrl": "https://startup.jobs/remote-jobs?w=remote&q=data+scientist",
    "results_wanted": 30,
    "max_pages": 3
}

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Sample Output

{
    "id": "8007953",
    "title": "Sr. Applied AI Engineer",
    "company": "Vi",
    "location": "Remote",
    "job_type": "Full Time",
    "posted_at": "2026-07-03T19:53:30Z",
    "company_logo": "https://startup.jobs/logos/38591",
    "apply_link": "https://startup.jobs/sr-applied-ai-engineer-vi-co-8007953",
    "url": "https://startup.jobs/sr-applied-ai-engineer-vi-co-8007953",
    "source": "listing-api",
    "fetched_at": "2026-07-09T14:07:36.988Z",
    "tags": ["Artificial Intelligence", "Engineer"],
    "workplace_type": "remote",
    "employment_type": "full-time",
    "experience_bucket": "3-6",
    "salary_currency": "USD",
    "country_code": "US",
    "country_id": 77,
    "company_id": 38591,
    "role_ids": [1, 8],
    "published_at_unix": 1783108410,
    "created_at_unix": 1783100100,
    "has_salary": false,
    "country": "United States",
    "company_slug": "vi-co"
}

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Tips for Best Results

Start Small

• Use results_wanted: 20 for quick validation.
• Increase result volume after checking the dataset shape.

Use Focused Searches

• Combine role and skill terms for targeted datasets.
• Use a custom listing URL when Startup.jobs filters already match your needs.

Review Missing Fields

• Some employers do not publish salary, city, or full descriptions.
• Check missing_fields when it appears to understand record-level gaps.

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Integrations

Connect your data with:

• Google Sheets - Review and share hiring data.
• Airtable - Build searchable recruiting databases.
• Make - Automate alerts and downstream workflows.
• Zapier - Trigger updates in CRM or notification tools.
• Webhooks - Send fresh run results to your systems.

Export Formats

• JSON - For data pipelines and apps.
• CSV - For spreadsheets and analysis.
• Excel - For reporting and operations.
• XML - For legacy integrations.

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Frequently Asked Questions

How many jobs can I collect?

You can collect up to 500 jobs per run using results_wanted.

Can I collect full job descriptions?

No, full descriptions are not included because the fast listing source does not publish them. The actor prioritizes stable listing records over slow page-detail collection.

Why are some fields missing?

Some companies do not publish every field, such as salary or city. Empty values are removed, and missing_fields appears if a core field is unavailable.

Can I schedule daily job monitoring?

Yes, schedule recurring runs in Apify to keep your dataset fresh.

Is the output ready for analysis?

Yes, records are structured, duplicate job IDs are skipped, and empty values are cleaned from each item.

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Support

For issues or feature requests, contact support through the Apify Console.

Resources

• Apify Documentation
• Apify API Reference
• Apify Scheduling

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Legal Notice

This actor is designed for legitimate data collection and analysis. Users are responsible for complying with applicable laws, website terms, and responsible data usage practices.