💼 BLS Occupation Projections Scraper

🚀 Export U.S. BLS 2024-2034 occupational projections in seconds. SOC code, occupation title, 2024 and 2034 employment, numeric and percent change, annual openings, median wage, typical education, and work experience - straight to CSV, Excel, JSON, or XML.

🕒 Last updated: 2026-05-26 · 📊 16 fields per record · 1,100+ occupations · 2024-2034 projection horizon

The BLS Occupation Projections Scraper turns the public Bureau of Labor Statistics Occupational Projections and Worker Characteristics table into a clean, structured dataset. It hits the same static HTML page the BLS publishes and parses every row - Summary, Major, Minor, Broad, and Detailed SOC levels - into a flat record per occupation.

Coverage spans the complete 2024-2034 employment projection: all 1,100+ occupations the BLS National Employment Matrix tracks, with employment counts (in thousands), growth numbers (numeric and percent), annual openings, median annual wage (USD), and the typical education and experience requirements for entry.

🎯 Target Audience	💡 Primary Use Cases
🎓 Career counselors	Recommend high-growth, high-wage occupations
📊 Workforce analysts	Track decade-out projections by SOC sector
🏢 HR / talent teams	Plan hiring against projected supply changes
📰 Journalists	Cite official BLS figures for occupation trend pieces
🤖 AI / ML teams	Train a career-recommendation engine on official numbers
🏛️ Policy researchers	Model labor market shifts by sector

📋 What the BLS Occupation Projections Scraper does

• Fetches the public BLS Occupational Projections HTML table.
• Parses every row (Summary, Major, Minor, Broad, and Detailed levels).
• Flattens each occupation into a 16-field record with occupationTitle first and error last.
• Applies optional filters: occupationType, minMedianWage, minEmploymentChangePercent.
• Exports as CSV, Excel, JSON, JSONL, XML, RSS, or HTML.

💡 Why it matters: the BLS publishes the projections as a 70-column wide HTML table that is painful to copy by hand. This actor flattens it into a structured dataset you can query, filter, and join.

🎬 Full Demo

🚧 Coming soon.

⚙️ Input

Field	Type	Required	Description
maxItems	integer	No	Free users: 10. Paid users: up to 1,000,000. The BLS table has ~1,100 rows total. Prefill: 10.
occupationType	enum	No	Filter by SOC hierarchy level: Summary, Major, Minor, Broad, Detailed, Line item. Leave empty for all.
minMedianWage	integer	No	Skip occupations whose median annual wage is below this value (USD).
minEmploymentChangePercent	number	No	Skip occupations growing slower than this percent over 2024-2034.

Example 1 - every detailed occupation:

{
  "maxItems": 1000,
  "occupationType": "Detailed"
}

Example 2 - high-growth, high-wage occupations:

{
  "maxItems": 200,
  "minMedianWage": 80000,
  "minEmploymentChangePercent": 5
}

⚠️ Good to Know: employment figures (employment2024, employment2034, employmentChangeNumeric, annualOpenings) are in thousands. medianAnnualWage is in USD. A - value in the source table is normalised to null.

📊 Output

Each record is a flat object. occupationTitle is first, error is last.

Field	Type	Description
💼 occupationTitle	string	Occupation title (BLS National Employment Matrix).
🆔 socCode	string	Standard Occupational Classification code.
🏷️ occupationType	string	SOC hierarchy level: Summary, Major, Minor, Broad, Detailed, Line item.
👷 employment2024	number	Employment in 2024, in thousands.
👷 employment2034	number	Projected employment in 2034, in thousands.
📈 employmentChangeNumeric	number	Numeric change 2024-2034, in thousands.
📈 employmentChangePercent	number	Percent change 2024-2034.
🧑‍💼 percentSelfEmployed	number	Percent self-employed, 2024.
📅 annualOpenings	number	Annual average occupational openings 2024-2034, in thousands.
💰 medianAnnualWage	number	Median annual wage, USD, 2024.
🎓 typicalEducation	string	Typical education needed for entry.
🛠️ workExperience	string	Work experience in a related occupation.
📚 onJobTraining	string	Typical on-the-job training needed.
🔗 oohUrl	string	Link to the Occupational Outlook Handbook page.
🔗 sourceUrl	string	The BLS source URL.
🕒 scrapedAt	ISO 8601	When this row was scraped.
❌ error	string|null	Per-record error (null on success).

Sample record:

{
  "occupationTitle": "Marketing managers",
  "socCode": "11-2021",
  "occupationType": "Detailed",
  "employment2024": 414.5,
  "employment2034": 441.7,
  "employmentChangeNumeric": 27.2,
  "employmentChangePercent": 6.6,
  "annualOpenings": 35.9,
  "medianAnnualWage": 161030,
  "typicalEducation": "Bachelor's degree",
  "workExperience": "5 years or more",
  "onJobTraining": "None",
  "oohUrl": "https://www.bls.gov/ooh/management/advertising-promotions-and-marketing-managers.htm",
  "sourceUrl": "https://www.bls.gov/emp/tables/occupational-projections-and-characteristics.htm"
}

✨ Why choose this Actor

✨ Feature	What it gets you
🇺🇸 Official BLS source	Straight from bls.gov, no third-party scraping.
📊 1,100+ occupations	Every SOC level the BLS publishes.
📅 2024-2034 horizon	Latest decade projection.
💰 Wage + education + experience	Filter by what matters to you.
🔗 OOH links included	Jump straight to the official career page for any row.
🆓 No API key	Public government data.

📈 How it compares to alternatives

Approach	Free?	Fields	Coverage	Effort
Manually copy from bls.gov	✅	All	All	Hours of clicking
BLS Public Data API	✅	Time-series only	Per-series, complex query	API key + series ID lookup
Commercial labor data vendor	❌	Full	Full	Subscription + integration
BLS Occupation Projections Scraper	✅ ($5 trial credit)	16	All 1,100+ occupations	1 click

🚀 How to use

1. Sign up. Create a free Apify account w/ $5 credit.
2. Open the BLS Occupation Projections Scraper page.
3. Set inputs. Set maxItems and any filters.
4. Run. Click Start. Free users get 10 items, paid users up to 1,000,000.
5. Export. Download the dataset as CSV, Excel, JSON, JSONL, XML, RSS, or HTML.

💼 Business use cases

🎓 Career advisory products

Power a "best jobs of the decade" widget on a career-advice site: filter for minEmploymentChangePercent: 10 and minMedianWage: 70000, then surface the top 25.

📊 Workforce planning

Pull every Detailed-level occupation, join against your internal headcount by SOC, and forecast hiring gaps decade-out.

🤖 AI career recommender

Use the dataset as a feature store for a career-recommendation model - wages, growth, education, experience, all standardised.

📰 Editorial / journalism

Cite official BLS figures with a single dataset URL instead of screenshotting a 70-column HTML table.

🔌 Automating BLS Occupation Projections Scraper

• Make (Integromat) - annual refresh when BLS publishes new projections.
• Zapier - push to Google Sheets on a schedule.
• Slack - share the dataset link with a team channel.
• Airbyte - sync into your warehouse.
• GitHub Actions - commit annual snapshots to a repo.
• Google Drive / Dropbox / S3 - drop the export into a folder.
• Webhooks - POST dataset URLs anywhere.

🌟 Beyond business use cases

🔬 Research

Compare 10-year projection accuracy across BLS releases. Study which sectors over- or under-projected.

🎮 Personal projects

"Should I switch careers?" calculators, side-by-side career comparison tools.

🤝 Non-profit / education

Teach students about the labor market with real BLS numbers. Workforce nonprofits can baseline interventions against projections.

🧪 Experimentation

Cluster occupations by growth + wage + education to discover non-obvious peer groups.

🤖 Ask an AI assistant about this scraper

Paste this into ChatGPT, Claude, Perplexity, or Copilot:

"Using the ParseForge BLS Occupation Projections Scraper dataset (filtered to Detailed-level occupations), shortlist the top 20 careers by employment growth percent that require only a Bachelor's degree and pay above $80,000 median."

❓ Frequently Asked Questions

🔑 Do I need a BLS API key?

No. The actor uses the public HTML table on bls.gov. No API key, no registration.

📅 What projection horizon does this cover?

2024-2034 - the BLS's current 10-year projection.

🧮 Are employment numbers in absolute jobs?

No - they are in thousands, as published by BLS. Multiply by 1,000 for raw counts.

💰 What currency is the median wage?

USD, 2024 dollars.

🆓 What do free users get?

Up to 10 items per run on a $5 trial credit. Paid users can pull up to 1,000,000 items (the full table is ~1,100 rows).

🔄 How often is the data refreshed?

Live on every run, but BLS itself updates the table on an annual cycle. The projection horizon shifts every release.

🏷️ What does occupationType mean?

SOC hierarchy level: Summary (totals), Major (2-digit), Minor (3-digit), Broad (4-digit), Detailed (6-digit), or Line item (special rollups).

🔗 What is the oohUrl?

Link to the BLS Occupational Outlook Handbook page for that occupation - duties, work environment, pay distribution, similar occupations.

🌍 Does this use proxies?

No proxies needed. bls.gov is a public government site.

⚠️ Is this affiliated with the BLS?

No. This is an independent tool. It is not endorsed by or affiliated with the U.S. Bureau of Labor Statistics or the Department of Labor.

📥 What export formats are available?

CSV, Excel (XLSX), JSON, JSONL, XML, RSS, and HTML.

🔌 Integrate with any app

Apify natively integrates with Make, Zapier, n8n, Slack, Discord, Airbyte, Keboola, Google Drive, Google Sheets, Dropbox, AWS S3, GitHub, GitLab, generic webhooks, and the Apify API / SDK (Python, JavaScript, CLI).

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💡 Pro Tip: browse the complete ParseForge collection for more reference and labor-market scrapers.

🆘 Need Help? Open our contact form

⚠️ Disclaimer: this is an independent tool, not affiliated with the U.S. Bureau of Labor Statistics or the Department of Labor. Only publicly available data from bls.gov is collected.