Indeed Scraper - Jobs, Salaries & Multi-Query AI Compare

Scrape job listings from Indeed, the world's largest job board, across 8 countries. Extract job titles, company names, salaries, descriptions, skills, benefits, and hiring signals. This Indeed scraper parses salary ranges automatically, detects 70+ technical and professional skills from job descriptions, and includes two AI-powered intelligence modes: single-query market analysis and multi-query x multi-location compare mode (new in v1.6) that builds a cross-role salary matrix, geo premium, and emerging-skill-gap report in a single run.

Whether you are a compensation team building multi-geo salary bands, a recruiter benchmarking 3 competing roles across 5 metros, or a career-switcher deciding between role pivots, this actor delivers structured Indeed data and AI-driven market intelligence without requiring you to stitch multiple scrapes together.

What it does

Indeed Scraper pulls structured job listings from Indeed across 8 countries (US, UK, Canada, Australia, Germany, France, Netherlands, India) and turns raw postings into decision-ready intelligence.

Every job is parsed into clean fields: normalized salary ranges (hourly/yearly/K-notation all resolved to min/max/period), 70+ detected technical and professional skills extracted from the job description, employer rating, benefits list, and job type. At $0.003 per deduplicated listing, it undercuts every competing Indeed scraper on Apify while shipping richer per-job structure.

The standout feature is multi-query compare mode (v1.6). Provide an array of job titles and an array of locations and the actor runs the full N×M grid in parallel — up to 16 cells — then sends all results to an LLM in one shot. The output is a single cross-role comparison report: a median salary matrix, geographic pay premium ranking, hottest skills across all roles, emerging skill gaps between titles, and per-audience recommendations. It also exports a CSV salary matrix and a Markdown executive briefing to the run's key-value store, ready to drop into a Slack workflow or weekly briefing.

For single-query runs, AI market analysis produces salary percentile bands (25th/50th/75th/90th), top-skill frequency ranking, company hiring-volume leaders, and remote/on-site ratio — all from a single $0.05 event charge.

Compensation teams, recruiters, HR analysts, career researchers, and workforce development organizations use it to replace hours of manual Indeed browsing with a scheduled, structured data pipeline.

Features

• 8-country support -- search Indeed across US, UK, Canada, Australia, Germany, France, Netherlands, and India using localized Indeed domains
• Multi-query compare mode (NEW in v1.6) -- supply queries[] + locations[] and the actor runs the full N x M grid in parallel (max 8 concurrent, capped at 16 cells), then an LLM produces a single cross-query / cross-location comparison report: median salary matrix, geo premium, hottest skills overall, emerging-skill gaps between roles, and per-audience recommendations
• Advanced job filters -- filter by date posted, job type (full-time, part-time, contract, internship), experience level (entry, mid, senior), salary minimum, and remote/hybrid/on-site
• Automatic salary parsing -- extracts and normalizes salary ranges from free-text salary strings, handling hourly rates, yearly salaries, K notation, and range formats into structured min/max/period fields
• 70+ skill detection -- scans title + job descriptions to identify mentioned technical skills (Python, AWS, Docker, React, SQL, Snowflake, dbt, LangChain, LLM, RAG, etc.) and professional skills, building a structured skills profile per job
• Benefits extraction -- captures listed benefits like health insurance, 401(k), remote work, PTO, and stock options
• Company ratings -- extracts employer rating scores from Indeed's company review system
• AI market intelligence (single-query) -- optional LLM-powered report with salary benchmarking (25th/50th/75th/90th percentiles), top skills by frequency, company hiring volume, remote vs on-site ratios, and actionable recommendations
• Compare-mode export artifacts (NEW in v1.7) -- render a CSV salary-matrix spreadsheet and/or a Markdown executive briefing to the run's key-value store, with a webhook for autonomous Slack/Notion delivery
• Multi-LLM support -- choose OpenRouter (recommended — 300+ models), Anthropic (Claude), Google AI (Gemini), OpenAI (GPT), or Ollama (self-hosted) for AI analysis
• Pay-per-event pricing -- only pay for what you scrape, no monthly fees or commitment

Use Cases

• Recruiters and staffing agencies (talent intelligence) -- benchmark competing offers across 3-8 metros in one run. The compare-mode salary matrix shows where the market is paying a premium for the role you're filling and which companies are hiring aggressively, so you can sharpen your pitch and pricing in a single weekly Slack briefing.
• HR and compensation teams (compensation benchmarking, alternative to Levels.fyi / Payscale) -- build data-driven compensation bands without a five-figure SaaS subscription. Levels.fyi and Payscale pull from self-reported employee data with a quarterly lag; this actor pulls live employer-posted salary ranges, normalizes hourly/yearly/K-notation, and emits 25/50/75/90 percentile bands per role and geography for ~$1 a run.
• Job seekers (geo arbitrage and role pivots) -- run the same query across 4-6 cities + Remote and let the geo-premium ranking show where your role pays 20-40% more for the same skill stack. Pair role pivot research (["data engineer", "ML engineer", "AI engineer"]) with the emerging-skill-gap report to see which adjacent role rewards your existing skills best.
• VCs and PE firms (hiring signals as portfolio diligence) -- monitor portfolio companies' hiring volume, role mix, and salary bands as a leading indicator of growth, pivots, or burn. Schedule weekly compare-mode runs across portfolio cohorts and feed the Markdown briefing straight into your investment-team Slack — cheaper and faster than LinkedIn Talent Insights ($1k+/month enterprise tier).
• Market researchers and equity analysts -- track hiring trends as a leading economic indicator. Run weekly ["software engineer", "sales", "operations"] comparisons across the FAANG cohort or any sector and track shifts in volume, salary growth, and remote ratio in a longitudinal dataset.
• Workforce-development organizations and bootcamps -- inform curriculum design with current skill demand. The 70+ skill detection library shows which programming languages, frameworks, and AI/ML tools are accelerating in your local market — informing course updates without buying a Burning Glass / Lightcast license.
• Talent acquisition leaders (alternative to LinkedIn Talent Insights / Glassdoor for Employers) -- LinkedIn Talent Insights starts at ~$1k/seat/month; Glassdoor for Employers bundles reviews with limited salary intelligence. This actor delivers structured cross-role/cross-geo salary + skill data on demand at $0.003/job, ready for direct ingestion into your BI stack or feeding Slack/Notion briefings via the included webhook.
• Salary researchers, academic economists, and consultants -- aggregate Indeed postings across roles, locations, experience levels, and time. Build longitudinal compensation databases for wage research, remote-work adoption studies, or client-facing market intelligence reports — at a fraction of the cost of API access from Indeed Hiring Lab or Burning Glass.

Input

Parameter	Type	Default	Description
searchQuery	string	-- (required in single-query mode)	Job title or keywords (e.g., "software engineer", "marketing manager")
queries	string[]	--	Compare mode: list of job titles to run in parallel. Requires locations also set.
locations	string[]	--	Compare mode: list of locations to run in parallel. Requires queries also set.
location	string	--	City, state, zip code, or "remote" (single-query mode only)
country	select	us	Indeed country domain: us, uk, ca, au, de, fr, nl, in
maxJobs	integer	25	Maximum jobs to scrape per cell (1-100). In compare mode this applies per (query, location) cell.
datePosted	select	7	Posting recency filter: 1 (24h), 3 (3 days), 7 (7 days), 14 (14 days), any
jobType	select	any	Job type: any, fulltime, parttime, contract, internship, temporary
experienceLevel	select	any	Experience: any, entry, mid, senior
salaryMin	integer	--	Minimum salary filter in local currency
remoteFilter	select	any	Work arrangement: any, remote, hybrid, in_person
sortBy	select	relevance	Sort by: relevance or date
fetchDetails	boolean	false	Backfill salary from job detail pages when the list card is missing it (common on sponsored/pagead cards like nursing roles). Adds ~1 extra request per missing-salary job. Off by default to keep runs fast.
exportFormat	select	none	Compare mode only: render a briefing artifact. Options: none, csv, markdown, both. Artifact stored as compare-{run_id}.csv / .md in the run's key-value store. Charged $0.01 per artifact.
artifactWebhookUrl	string	--	Compare mode only: optional HTTPS webhook to POST artifact URLs after generation. Wire to Slack / Zapier / Make for autonomous weekly compensation briefings. Non-fatal on failure.
enableAiAnalysis	boolean	false	Generate AI market intelligence report (single-query) or comparison report (compare mode)
llmProvider	select	openrouter	AI provider: openrouter, anthropic, google, openai, or ollama
llmModel	string	--	Override default LLM model (leave empty for recommended default)
openrouterApiKey	string	--	OpenRouter API key (required if using OpenRouter)
anthropicApiKey	string	--	Anthropic API key (required if using Anthropic)
googleApiKey	string	--	Google AI API key (required if using Google AI)
openaiApiKey	string	--	OpenAI API key (required if using OpenAI)
ollamaBaseUrl	string	http://localhost:11434	Ollama base URL (required if using Ollama)
proxyConfiguration	proxy	RESIDENTIAL	Proxy settings. Indeed aggressively blocks datacenter IPs — RESIDENTIAL is strongly recommended.

Full Example Input

{
    "searchQuery": "software engineer",
    "location": "San Francisco, CA",
    "country": "us",
    "maxJobs": 25,
    "datePosted": "7",
    "jobType": "fulltime",
    "experienceLevel": "mid",
    "remoteFilter": "any",
    "sortBy": "relevance",
    "enableAiAnalysis": true,
    "llmProvider": "openrouter",
    "openrouterApiKey": "sk-or-..."
}

Output

Each job is pushed as a separate dataset item:

{
    "job_id": "abc123def456",
    "title": "Senior Software Engineer",
    "company_name": "TechCorp Inc.",
    "company_rating": 4.2,
    "location": "San Francisco, CA",
    "is_remote": false,
    "salary_text": "$150,000 - $200,000 a year",
    "salary_min": 150000,
    "salary_max": 200000,
    "salary_period": "yearly",
    "salary_currency": "USD",
    "currency": "USD",
    "job_type": "full-time",
    "description_snippet": "We are looking for a Senior Software Engineer to join...",
    "posted_date": "2026-04-08",
    "job_url": "https://www.indeed.com/viewjob?jk=abc123def456",
    "url": "https://www.indeed.com/viewjob?jk=abc123def456",
    "benefits": ["Health insurance", "401(k)"],
    "skills_mentioned": ["Python", "AWS", "Docker", "Kubernetes", "React"],
    "search_query": "software engineer",
    "search_location": "San Francisco, CA",
    "search_country": "us",
    "scraped_at": "2026-04-10T12:00:00+00:00"
}

Output field reference

Field	Type	Description
job_id	string	16-char Indeed job key (e.g. d55eb1a8c9e4bbe8)
title	string	Job title as posted
company_name	string	Employer name
company_rating	float	Indeed employer rating (1.0-5.0) when available
location	string	City, state / region as posted
is_remote	boolean	True if the listing is tagged remote
salary_text	string	Raw salary string from the listing
salary_min / salary_max	number	Parsed numeric salary range
salary_period	string	hourly, daily, weekly, monthly, or yearly
salary_currency	string	ISO-ish currency code (USD, GBP, EUR, etc.) — legacy field
currency	string	Portfolio-standard ISO 4217 currency code — prefer this
job_type	string	full-time, part-time, contract, internship, temporary
description_snippet	string	First ~500 chars of the job description
posted_date	string	ISO 8601 date derived from Indeed's "X days ago" label
job_url	string	Direct viewjob?jk=... link — legacy field
url	string	Portfolio-standard URL field — prefer this
benefits	string[]	Extracted perk labels (health, 401k, RSU, etc.)
skills_mentioned	string[]	70+ tech + business skills detected in title + description
search_query / search_location / search_country	string	Echo of the original request
scraped_at	string	ISO 8601 UTC timestamp

Field migration note: salary_currency and job_url are retained for backward compatibility, but both dual-emit the portfolio-standard currency and url alongside. New integrations should read currency and url; legacy names will be dropped in a future release.

AI Market Intelligence Output

When enableAiAnalysis is enabled, an additional dataset item contains a comprehensive market report including:

• Salary benchmarking -- 25th, 50th, 75th, and 90th percentile salary ranges for the searched role
• Top skills by frequency -- ranked list of the most mentioned technical and professional skills
• Company hiring volume -- which companies are posting the most jobs and at what salary levels
• Remote vs on-site ratios -- breakdown of work arrangement preferences in the market
• Top-paying listings -- highest compensation packages with company and requirements details
• Market temperature -- hiring velocity, competition level, and demand indicators
• Actionable recommendations -- tailored advice for job seekers, recruiters, and hiring managers

Cost and Pricing

This actor uses Apify's pay-per-event pricing model. You only pay for what you scrape — no monthly fees, no commitments.

Event	Price	Description
job-scraped	$0.003	Charged per deduplicated job listing extracted
ai-analysis-completed	$0.05	Charged when a single-query AI market intelligence report is generated
market-comparison-report	$0.10	Charged when a multi-query compare-mode report is generated
export-csv-generated	$0.01	Charged per compare-mode CSV salary-matrix artifact
export-markdown-generated	$0.01	Charged per compare-mode Markdown briefing artifact

Scenario	Jobs	AI Event	Export	Total Cost
Quick salary check	10	none	none	$0.03
Role market analysis (single query)	25	$0.05 ai-analysis	none	$0.125
Full market intelligence (single query)	50	$0.05 ai-analysis	none	$0.20
Large-scale data collection	100	$0.05 ai-analysis	none	$0.35
Compare 3 roles x 4 cities at 25/cell	300	$0.10 comparison	none	$1.00
Weekly Slack briefing: 3 roles x 4 cities	300	$0.10 comparison	CSV+MD ($0.02)	$1.02
Daily Slack tracker: 2 roles x 3 cities	150	$0.10 comparison	CSV+MD ($0.02)	$0.57

How we compare to other Indeed scrapers on Apify

Scraper	Price	Model	AI Analysis
This actor	$3/1K jobs + $0.05/AI report	Pay-per-event, no base fee	Yes (5 providers)
misceres/indeed-scraper	$3/1K	Pay-per-result	No
borderline/indeed-scraper	$5/1K	Pay-per-result	No
memo23/apify-indeed-cheerio	$29/month + usage	Rental + usage	No
curious_coder/indeed-scraper	$20/month + usage	Rental + usage	No

Quick Start

The simplest way to get started -- search for a single job title:

{
    "searchQuery": "data scientist",
    "location": "New York, NY",
    "maxJobs": 10
}

This scrapes the top 10 data scientist job listings in New York sorted by relevance.

Weekly Comp-Briefing Template (one-click clone)

Saves a recurring task that runs every Monday 8am, comparing 3 roles x 3 locations, exports to CSV + Markdown, posts the briefing to your Slack via webhook.

{
  "queries": ["data engineer", "ML engineer", "AI engineer"],
  "locations": ["New York, NY", "San Francisco, CA", "Remote"],
  "country": "us",
  "datePosted": 7,
  "compareMode": true,
  "exportFormat": "both",
  "enableAiAnalysis": true,
  "aiProvider": "openrouter",
  "artifactWebhookUrl": "https://hooks.slack.com/services/YOUR/WEBHOOK/HERE",
  "maxJobs": 50
}

1. Open the actor in Apify Console.
2. Click "Save & Build".
3. Paste the JSON above into Input.
4. Set Schedule -> Cron 0 8 * * MON.
5. Replace the webhook URL with your Slack incoming webhook.

Cost callout: Each weekly run: ~$1.02 (50 jobs x $0.003 + 3 compare reports x $0.10 + CSV+MD exports + AI). Annual cost: ~$53 vs ~$1,200/yr for Levels.fyi Insights team license.

Multi-Query Compare Mode (v1.6+)

Supply queries and locations as arrays to run the full N x M grid in one job and get a single cross-role / cross-location AI comparison report:

{
    "queries": ["data scientist", "ML engineer", "AI researcher"],
    "locations": ["New York, NY", "San Francisco, CA", "Austin, TX", "Remote"],
    "country": "us",
    "maxJobs": 25,
    "enableAiAnalysis": true,
    "llmProvider": "openrouter",
    "openrouterApiKey": "sk-or-..."
}

The actor runs 3 x 4 = 12 parallel searches (max 8 concurrent), writes every job to the dataset tagged with its search_query and search_location, and pushes a market_comparison_report item containing the median-salary matrix, highest-paying combinations, geo premium analysis, hottest skills overall, and emerging-skill gaps between roles. Grid is capped at 16 cells to protect proxy budget.

Compare mode charges a single $0.10 market-comparison-report event in place of the $0.05 ai-analysis-completed event.

Compare-Mode Export Artifacts (v1.7+)

Autonomous weekly compensation briefings. Set exportFormat to "csv", "markdown", or "both" and the actor renders a ready-to-share artifact on top of the raw dataset:

• "csv" -- RFC-4180 salary-matrix spreadsheet. Loads cleanly into Google Sheets, Tableau, Power BI, Excel.
• "markdown" -- README-style executive brief designed for direct paste into Slack / Notion / email.
• "both" -- emit both. Charged $0.01 per artifact.

Each artifact is stored in the run's default key-value store as compare-{run_id}.csv / .md and the public URL is included as an export_artifact dataset item.

Pair with the optional artifactWebhookUrl input and Apify Scheduler for an autonomous weekly comp-briefing pipeline:

{
    "queries": ["data scientist", "ML engineer"],
    "locations": ["New York, NY", "San Francisco, CA", "Remote"],
    "country": "us",
    "maxJobs": 25,
    "enableAiAnalysis": true,
    "llmProvider": "openrouter",
    "openrouterApiKey": "sk-or-...",
    "exportFormat": "both",
    "artifactWebhookUrl": "https://hooks.slack.com/services/T00/B00/XXXX"
}

Every Monday at 8 AM, the actor scrapes 2 roles x 3 cities, writes a Markdown brief + CSV matrix to key-value storage, and POSTs the URLs to your Slack / Zapier / Make webhook. Weekly $1.02; daily $0.57.

More Examples

Basic job search — scrape software engineer jobs in San Francisco:

{
    "searchQuery": "software engineer",
    "location": "San Francisco, CA",
    "maxJobs": 25,
    "country": "us"
}

Multi-query market research — compare salaries across roles in one city:

{
    "queries": ["data scientist", "machine learning engineer", "AI researcher"],
    "locations": ["New York, NY"],
    "maxJobs": 10,
    "country": "us"
}

Remote jobs with AI analysis — find remote Python developer jobs and get market intelligence:

{
    "searchQuery": "Python developer remote",
    "maxJobs": 50,
    "enableAiAnalysis": true,
    "llmProvider": "openrouter",
    "openrouterApiKey": "YOUR_KEY"
}

Troubleshooting

Getting blocked or 0 results returned Indeed uses aggressive bot detection (CAPTCHA, rate limits). Always set proxyConfiguration with RESIDENTIAL proxy group. Run with a low maxJobs (10-20) first to verify the proxy is working. US proxies work best for indeed.com; match country to your target Indeed domain.

Salary data missing for most jobs Salary is employer-provided and often not disclosed. Indeed reports that only ~30-40% of job postings include salary data. The actor captures salary when present; missing salary results in null fields, not an error. Enable fetchDetails to backfill salary from job detail pages for sponsored listings that omit salary on the list card.

Jobs appear duplicated across result pages Indeed sometimes serves the same promoted job listing on multiple search pages. The actor deduplicates by job_id within a single run. If you run multiple queries, cross-run dedup is your responsibility (use job_id as the unique key).

AI comparison fails for multi-query runs AI cross-role salary matrix requires multiple entries in queries to be set. With only one query, AI analysis runs in single-role mode (no salary matrix). Set at least 2 different job titles in queries to activate cross-role comparison.

CSV/Markdown export not appearing in dataset CSV and Markdown exports are pushed as special _type: "export" items to the dataset. They won't appear in the standard dataset view's item count — check the raw dataset JSON for items where _type === "export". Download via the Apify API: GET /v2/datasets/{id}/items?format=json.

Indeed bot detection — persistent failures Indeed uses sophisticated bot detection including behavioral analysis, CAPTCHA challenges, and IP reputation scoring. If you experience persistent 403 errors: (1) ensure you are using RESIDENTIAL proxies, not datacenter; (2) try a lower maxJobs (10-15 per cell); (3) try again later as proxy IP pools rotate; (4) try a different country domain. There is no guaranteed workaround — residential proxies achieve ~80-90% success rates on most queries.

Frequently Asked Questions

How accurate is the salary data? The actor extracts salary information directly from Indeed job postings. Salary data is only available for jobs that include salary in their listings -- typically 30-60% of postings depending on the role and market. The automatic parser normalizes all formats (hourly, yearly, K notation, ranges) into consistent structured fields.

Which countries are supported? The actor supports 8 Indeed country domains: United States (us), United Kingdom (uk), Canada (ca), Australia (au), Germany (de), France (fr), Netherlands (nl), and India (in). Each country uses the localized Indeed domain for accurate local results.

How does skill detection work? The actor scans job titles + description snippets against a library of 70+ technical and professional skills including programming languages (Python, Java, JavaScript, .NET), cloud platforms (AWS, Azure, GCP), data/ML tooling (Snowflake, Databricks, Airflow, dbt, TensorFlow, PyTorch), frameworks (React, Next.js, Django, Spring), infra (Docker, Kubernetes, Terraform, Ansible), modern AI stack (OpenAI, LangChain, LLM, RAG), and tools (Jira, Figma, Salesforce, SAP).

How does compare mode work? Set queries (e.g. ["data scientist", "ML engineer", "AI researcher"]) and locations (e.g. ["New York, NY", "San Francisco, CA", "Remote"]) instead of the single searchQuery / location fields. Arrays take precedence. The actor runs the full N x M grid of searches in parallel (8 concurrent, capped at 16 cells), tags every job with its search_query and search_location, and — if enableAiAnalysis is true — produces a single market_comparison_report with a median-salary matrix, highest-paying combinations, geo premium analysis, hottest skills, and emerging skill gap callouts.

Can I track hiring trends over time? Yes. Schedule regular runs on Apify (weekly or monthly) for the same search queries and locations. Over time, you build a longitudinal dataset showing changes in job volume, salary ranges, skill demand, and remote work adoption.

Legal and Compliance

This actor scrapes publicly available data. By using this actor, you agree to the following:

• Your responsibility: You are solely responsible for ensuring your use complies with all applicable laws, regulations, and the target website's terms of service. This includes but is not limited to GDPR (EU), CCPA (California), and other data protection laws in your jurisdiction.
• No legal advice: This actor does not constitute legal advice. Consult a qualified attorney if you have questions about the legality of your specific use case.
• Intended use: This actor is designed for legitimate business purposes such as market research, competitive analysis, and academic research using publicly accessible data.
• Data handling: You are responsible for how you store, process, and share any data collected. Ensure you have a lawful basis for processing any personal data under applicable privacy laws.
• Rate limiting: This actor implements polite crawling practices including request delays and retry backoff to minimize impact on target servers.
• No warranty: This actor is provided "as is" without warranty. Data accuracy depends on the target website's content and structure.
• Job data: Indeed's terms of service restrict automated data collection. Job listings are provided for informational and research purposes. Do not use scraped data to create competing job board services.
• Personal data notice: Job listings may contain names of hiring managers or company representatives. Under GDPR and similar regulations, even publicly available personal data may be subject to data protection requirements. Ensure you have a lawful basis (such as legitimate interest) for collecting and processing this data. Implement appropriate data retention policies.

Limitations

• Indeed aggressively blocks automated access. Residential proxies are required and even then, some requests may be blocked. The actor rotates proxy IPs between retries with exponential backoff. If you experience persistent 403 errors, try running again (different proxy IPs may succeed) or try a different country domain.
• Salary data is only available for jobs that include salary information in their listings (not all do).
• Skills detection is based on pattern matching from job description snippets, not full job descriptions -- some skills may be missed.
• AI analysis quality depends on the number of jobs scraped (25+ recommended) and the LLM model chosen.
• Indeed's HTML structure may change; the actor uses multiple parsing strategies for resilience but temporary disruptions are possible.
• Maximum 100 jobs per run to maintain reasonable resource usage.
• Job posting recency depends on Indeed's internal date tracking, which may not always be precise.

Tips for Reliable Runs

• Use specific job titles. "Senior Data Engineer" returns more targeted results than generic terms like "data" or "engineer."
• Filter by date posted. Set datePosted to 7 or 3 to focus on active, current openings rather than stale listings.
• Enable AI analysis for salary benchmarking. The AI report synthesizes salary data across all scraped jobs into actionable percentile ranges.
• Scrape 25+ jobs for meaningful insights. Both skill detection patterns and AI analysis improve significantly with more data points.
• Compare across locations. Run the same search query in multiple cities to understand geographic salary differences.
• Use residential proxies for large runs. For scraping 50+ jobs, residential proxies improve reliability.

Implementation Notes

• Uses HTTP requests with rotating User-Agents (no browser required for basic scraping)
• Parses Indeed's server-rendered HTML with multiple extraction strategies for resilience
• Automatic salary parser handles formats like "$150K-$200K", "$45/hr", "$150,000 - $200,000 a year"
• Skills detection uses a curated library of 70+ patterns matching common technical, data/ML, and professional skills
• AI analysis sends aggregated job statistics to the LLM -- individual job descriptions are not sent in full
• Supports Apify proxy with automatic proxy URL detection from environment variables

Related Actors

Pair this actor with others from the same portfolio for richer pipelines:

• Contact Extractor — Enrich Indeed company data with hiring-manager contacts. Feed each listing's company website through Contact Extractor to get SMTP-verified emails, direct phones, and tech-stack signals — turning a job board into a recruiter sourcing pipeline.
• News Monitor — Track funding rounds, expansions, and layoff news for the companies hiring on Indeed. Combine recent press with active job postings to spot growth-stage employers and time applications (or recruiter outreach) around real-world hiring momentum.
• Reddit Scraper — Pull employer reputation signals from subreddits like r/cscareerquestions, r/recruitinghell, and company-specific threads. Cross-reference Indeed listings with employee sentiment to filter out toxic workplaces before you apply or shortlist candidates.