H-1B Employer Scraper — Sponsoring Company Leads avatar

H-1B Employer Scraper — Sponsoring Company Leads

Deprecated

Pricing

from $8.00 / 1,000 leads

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H-1B Employer Scraper — Sponsoring Company Leads

H-1B Employer Scraper — Sponsoring Company Leads

Deprecated

Scrape the US DOL OFLC quarterly LCA disclosure data to find top H-1B visa sponsoring companies. Returns deduplicated employer leads with address, NAICS industry, application volume, certification rate, and wage ranges.

Pricing

from $8.00 / 1,000 leads

Rating

0.0

(0)

Developer

GoCreative AI

GoCreative AI

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

4 minutes ago

Last modified

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Scrape the US DOL OFLC quarterly LCA disclosure data to find top H-1B visa sponsoring companies. Returns deduplicated employer leads with address, NAICS industry, application volume, certification rate, and wage ranges.

No API key, no signup, no subscription — pay only for what you scrape. Clean, structured output ready for CSV, JSON, Excel, or direct API export into your own pipeline.

What this scraper does

Scrape the US DOL OFLC quarterly LCA disclosure data to find top H-1B visa sponsoring companies. Returns deduplicated employer leads with address, NAICS industry, application volume, certification rate, and wage ranges.

Every run pulls fresh data straight from the source and pushes clean, typed records to the dataset — ready for your CRM, spreadsheet, AI agent, or data pipeline.

Use cases

  • B2B lead generation — build targeted prospect lists with verified, structured data
  • Sales prospecting — find companies and contacts that match your ICP
  • Market research & competitive intelligence — track an industry or niche in structured form
  • AI agents & automation — feed agents clean external data without scraping infra
  • Data enrichment — append fresh fields to your existing lists

Input

FieldDescription
quarterWhich DOL OFLC quarterly LCA disclosure dataset to download. Follows US federal fiscal year (FY starts Oct 1). Use the most recent published
max_rowsMaximum number of application rows to read from the disclosure file. Higher values yield more unique employers but increase runtime. Full qu
max_resultsMaximum number of unique employer records to output, sorted by total H-1B application count descending.
naics_filterFilter employers by NAICS code prefix. Examples: 51 = Information/Tech, 54 = Professional Services, 52 = Finance. Leave blank to include all
state_filterFilter employers by 2-letter US state code (e.g. CA, TX, NY). Leave blank to include all states.

Output

Every result is a clean structured record. Export the full dataset as CSV, JSON, or Excel from the Apify console, or pull it via the Apify API straight into your own tools.

Why use this actor

  • Scrape dol h1b employer leads — fast, structured, reliable.
  • Dol h1b employer leads data export (csv, json, excel) — fast, structured, reliable.
  • Dol h1b employer leads api alternative — no key required — fast, structured, reliable.
  • Automated dol h1b employer leads monitoring on a schedule — fast, structured, reliable.
  • Structured dol h1b employer leads records for ai agents and pipelines — fast, structured, reliable.

How it works

This actor pulls data directly from the source, structures it into clean rows, and pushes each result to the dataset. It runs on Apify's infrastructure — reliable, schedulable, and pay-per-result so you only pay for data you actually get.

Pricing

Pay-per-result via the Apify Store. No monthly subscription, no minimums — run it once or schedule it daily; you're only charged for the results returned.

FAQ

Do I need an API key or account? No. Just provide your input and run it.

Can I schedule it to run automatically? Yes — use Apify Schedules to run it hourly, daily, or weekly and get fresh data on autopilot.

What formats can I export? CSV, JSON, Excel, or via the Apify API.

Can I integrate it into my own app? Yes — call it via the Apify API and pull results directly into your pipeline.

Is the data accurate and fresh? Data is pulled live from the source on each run, so it reflects what's available at run time.