Hiring Signal Tracker — Hedge Fund Alternative Data

Turn any company's career page into a structured hiring signal. Built for hedge funds, quant traders, and competitive intel teams that need to predict company growth before earnings.

This actor tracks job posting volume and composition across companies, returning structured signals (total openings, role mix, seniority distribution, geographic spread, remote percentage, recent additions) that hedge funds use as a leading indicator of company health.

What does Hiring Signal Tracker do?

You give it a list of companies and their careers page URLs. It auto-detects which ATS (applicant tracking system) each company uses — Greenhouse, Lever, Ashby, Workday, Rippling — and pulls the full job board via the official ATS API where possible. For companies with no recognizable ATS it falls back to generic HTML scraping.

For each company it returns:

• Total open positions (the headline signal)
• Department mix: engineering, sales, marketing, operations, design, data, product, customer success — as both counts and percentages
• Seniority mix: intern / junior / mid / senior / staff / principal / director / VP / C-level
• Top locations (top 10 cities/regions by job count)
• Remote job count (and percentage)
• New jobs in the last 7 days (delta tracking signal)
• Sample titles (first 10 job titles for spot-checking)

Why use Hiring Signal Tracker?

The alternative data market is $17 billion by 2027. 78% of hedge funds now incorporate alternative data into their strategies (Nasdaq State of Alternative Data 2025). Job posting trends are one of the most validated alt data signals — they predict revenue growth, M&A activity, and strategic pivots months ahead of earnings calls.

Hedge funds and quant traders use this to:

• Predict revenue growth (sales-team hiring → revenue growth in 2 quarters)
• Detect strategic pivots (engineering ratio jumping → new product line)
• Spot cost cuts before they hit earnings (hiring freeze → margin compression)
• Geographic expansion signals (new city in top locations → new market entry)
• M&A integration tracking (post-merger hiring patterns)

Competitive intel teams use this to:

• Track competitor org growth
• Identify which functions a competitor is investing in
• Predict competitive product launches based on engineering hiring spikes

HR / recruiting tech vendors use this to:

• Monitor industry hiring trends
• Build customer-facing competitor benchmarks
• Identify high-growth target accounts

Job board aggregators use this to:

• Source job listings at scale
• Detect new postings within 24h of being published

How to use

1. Click Try for free (or Start)
2. Paste the JSON list of companies into Companies (just name + careersUrl for each)
3. Click Start
4. Download as JSON, CSV, HTML, or Excel — or schedule daily runs

Input

{
    "companies": [
        { "name": "Stripe", "careersUrl": "https://stripe.com/jobs", "ats": "autodetect" },
        { "name": "Anthropic", "careersUrl": "https://www.anthropic.com/careers", "ats": "autodetect" },
        { "name": "Notion", "careersUrl": "https://www.notion.so/careers", "ats": "autodetect" }
    ],
    "classifyRoles": true,
    "extractLocations": true,
    "extractSeniority": true
}

• companies — array of { name, careersUrl, ats } objects (ats can be autodetect or one of greenhouse | lever | ashby | workday | rippling)
• classifyRoles — auto-classify into departments (default: yes)
• extractLocations — aggregate by city/region (default: yes)
• extractSeniority — classify into intern/junior/mid/senior/etc. (default: yes)

Output

{
    "company": "Stripe",
    "ats": "greenhouse",
    "careersUrl": "https://stripe.com/jobs",
    "totalJobs": 487,
    "departments": {
        "engineering": 195,
        "sales": 64,
        "marketing": 32,
        "operations": 58,
        "design": 28,
        "data": 41,
        "product": 22,
        "customer": 47
    },
    "seniorityMix": {
        "junior": 12,
        "mid": 215,
        "senior": 178,
        "staff": 52,
        "principal": 18,
        "director": 8,
        "vp": 4
    },
    "topLocations": [
        "Remote (124)",
        "San Francisco (98)",
        "Dublin (72)",
        "London (54)",
        "New York (48)",
        "Toronto (32)",
        "Singapore (28)",
        "Chicago (18)",
        "Tokyo (12)",
        "Berlin (10)"
    ],
    "remoteJobs": 124,
    "engineeringPercent": 40,
    "salesPercent": 13,
    "newJobs": 47,
    "snapshotAt": "2026-04-15T20:00:00.000Z",
    "sampleTitles": [
        "Staff Software Engineer, Payments",
        "Senior Account Executive, Enterprise",
        "Engineering Manager, Treasury",
        "Product Designer, Identity",
        "Data Scientist, Risk"
    ]
}

Data table

Field	Type	Description
company	string	Company name as you provided it
ats	string	Detected ATS (greenhouse / lever / ashby / workday / generic)
careersUrl	string	The URL crawled
totalJobs	number	Total open positions
departments	object	Job counts by department
seniorityMix	object	Job counts by seniority level
topLocations	array	Top 10 cities by job count, formatted as "City (count)"
remoteJobs	number	Number of remote jobs
engineeringPercent	number	Engineering jobs as % of total
salesPercent	number	Sales jobs as % of total
newJobs	number	Jobs posted in the last 7 days (only available for ATS-backed companies)
snapshotAt	string	ISO timestamp
sampleTitles	array	First 10 job titles for spot-checking

Pricing

This actor uses pay-per-event pricing — perfect for tracking many companies at once:

• Actor start: $0.05 per run
• Per company tracked: $0.10 per company

Example costs:

• 1 company snapshot → $0.15
• Daily snapshot of 50 portfolio companies → ~$5/day = $150/month
• Weekly snapshot of the S&P 500 → ~$50/week = $200/month
• Quarterly snapshot of 1,000 private companies for diligence → ~$100/quarter

Compare to Revelio Labs ($15k/year base), Thinknum ($50k/year), or LinkUp Data (~$80k/year). For most use cases this actor is dramatically cheaper.

Free Apify tier members get $5/month in platform credits, which covers ~50 company snapshots per month.

Tips and advanced options

• Schedule daily runs to build a hiring time series — diff the daily snapshots downstream to detect changes
• Track competitors quarterly for competitive intel reports
• Combine with SEC EDGAR Filing Monitor to correlate hiring spikes with material disclosures
• Pipe into a quant model to test hiring signal as an alpha factor
• Use ATS-specific input ("ats": "greenhouse") to skip auto-detection and save 1 HTTP request per company

Supported ATS systems

ATS	API	Coverage
Greenhouse	boards-api.greenhouse.io (official, free)	Full structured data
Lever	api.lever.co (official, free)	Full structured data
Ashby	api.ashbyhq.com/posting-api (official)	Full structured data
Workday	(HTML scraping only)	Title + location
Rippling	(HTML scraping only)	Title + location
Generic HTML	(heuristic scraping)	Job titles, basic counts

FAQ and support

Is the data real-time? Greenhouse, Lever, and Ashby APIs return data within minutes of jobs being posted/closed. Generic HTML pages are eventually consistent.

What about LinkedIn jobs? LinkedIn aggressively blocks scrapers and our actor does not target their site. For LinkedIn-specific data, use a dedicated LinkedIn jobs scraper.

Is this legal? All ATS APIs we use (Greenhouse, Lever, Ashby) are publicly documented and free for commercial use. The companies themselves publish job listings to be discovered. We respect rate limits and identify ourselves with a clear User-Agent.

Can I track private companies? Yes — many private companies use Greenhouse / Lever / Ashby and have publicly browsable job boards. The actor handles them just as well as public companies.

Found a bug? Open an issue on the Issues tab.