Introducing Job Posting Datasets: Uncover labor market insights!

Elevate your recruitment strategies, forecast future labor industry trends, and unearth investment opportunities with Job Posting Datasets.

Job Posting Datasets Source:

1. Indeed: Access datasets from Indeed, a leading employment website known for its comprehensive job listings.

2. Glassdoor: Receive ready-to-use employee reviews, salary ranges, and job openings from Glassdoor.

3. StackShare: Access StackShare datasets to make data-driven technology decisions.

Job Posting Datasets provide meticulously acquired and parsed data, freeing you to focus on analysis. You'll receive clean, structured, ready-to-use job posting data, including job titles, company names, seniority levels, industries, locations, salaries, and employment types.

Choose your preferred dataset delivery options for convenience:

Receive datasets in various formats, including CSV, JSON, and more. Opt for storage solutions such as AWS S3, Google Cloud Storage, and more. Customize data delivery frequencies, whether one-time or per your agreed schedule.

Why Choose Oxylabs Job Posting Datasets:

1. Fresh and accurate data: Access clean and structured job posting datasets collected by our seasoned web scraping professionals, enabling you to dive into analysis.

2. Time and resource savings: Focus on data analysis and your core business objectives while we efficiently handle the data extraction process cost-effectively.

3. Customized solutions: Tailor our approach to your business needs, ensuring your goals are met.

4. Legal compliance: Partner with a trusted leader in ethical data collection. Oxylabs is a founding member of the Ethical Web Data Collection Initiative, aligning with GDPR and CCPA best practices.

Pricing Options:

Standard Datasets: choose from various ready-to-use datasets with standardized data schemas, priced from $1,000/month.

Custom Datasets: Tailor datasets from any public web domain to your unique business needs. Contact our sales team for custom pricing.

Experience a seamless journey with Oxylabs:

• Understanding your data needs: We work closely to understand your business nature and daily operations, defining your unique data requirements.
• Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
• Delivering data sample: We provide a sample for your feedback on data quality and the entire delivery process.
• Continuous data delivery: We continuously collect public data and deliver custom datasets per the agreed frequency.

Effortlessly access fresh job posting data with Oxylabs Job Posting Datasets.

Main labour market statistics time series data (large dataset).

The Online Recruitment Sites industry has boomed since the 2000s as job searches have moved online and the internet has become an indispensable part of daily life. The internet has become the primary medium for communicating and accessing information, the main driving force behind this industry's rise. Job seekers and employers have increasingly turned to online recruitment sites to look for new openings and find new talent pools.The largest online recruitment sites have grown through organic innovation and by acquiring competitors targeting niche industries. Historically, incumbents held a competitive advantage in developing brand names, making it difficult for new sites to gain market share. Nonetheless, low barriers to entry have upended the industry as once-dominant platforms like Monster and CareerBuilder have lost relevance, and LinkedIn has become the overwhelming market-leader by leveraging technological innovation. Online job portals have become the primary tool for matching candidates to employers, with the pandemic only furthering the online shift as businesses embrace digital talent sourcing. In this environment, industry revenue is forecast to grow at a CAGR of 6.2% to $18.8 billion through 2025, including 6.4% in 2025 alone. Profitability has widened too, despite heavy ongoing investments in technology, with platforms relying on premium services to bring in recurring revenue streams.Driven by the rapid development of artificial intelligence and machine learning to automate resume screening, candidate sourcing and chat-based engagement, online recruitment sites will provide a broader range of services that go well beyond standard job posting services and resume collection. Predictive analytics will be central to the transformation of talent acquisition by replacing manual screening, helping recruiters compete more effectively with in-house hiring departments. Online recruitment sites will continue to evolve into professional networking platforms, becoming comprehensive career ecosystems. With a steady labor market poised to see growth in key sectors like healthcare and technology, revenue across online recruitment sites is forecast to grow at a CAGR of 5.6% to $24.8 billion through 2030.

Sampling variability and revisions analyses for countries and regions of the UK, including employment, unemployment, economic inactivity and Claimant Count, rolling three-monthly figures.

The Australian Government Department of Jobs and Small Business publishes a range of labour market data on its Labour Market Information Portal website (lmip.gov.au).

The link below provides data for the boundaries used by the Department in its administration of jobactive. These boundaries are known as Employment Regions. The data provided includes:

• jobactive caseload data (Australian Government Department of Employment administrative data);
• Centrelink administrative data - Australian Government Department of Employment extract;
• Unemployment rates (Australian Bureau of Statistics Labour Force Survey data and Australian Government Department of Employment estimates, derived from Small Area Labour Markets estimates);
• Employment by industry and occupation (Australian Bureau of Statistics Labour Force Survey data and Census of Population and Housing data);
• Population by age group data (Australian Bureau of Statistics Labour Force Survey data and Australian Bureau of Statistics Estimated Resident Population).

Data tables on the number of jobs in Jersey. These are reported on in the Jersey labour market report, which is published every six months and covers key aspects of both public and private sector employment. The latest labour market reports can be found here.

LinkUp Raw contains the most complete set of LinkUp’s job market data, dating back to 2007. The dataset includes full job postings sourced directly from employer websites as well as statistics and analysis of the job postings. Delivered daily, LinkUp Raw consists of 4 distinct components: individual job records, individual descriptions, core aggregates, and company reference data.

The dataset includes over 20 unique job and company level attributes and identifiers, such as, job title, full job description, job URL, company name, location, occupation code, sector code, ticker, reference data, and more.

Use Cases for Job Market Data:

-Rely on a unique, timely, and accurate job listings dataset sourced directly from employer websites globally. LinkUp collects, refines, and distributes data to deliver insightful, predictive, and actionable job market information.

-Perform deeper analysis with extensive global coverage, irreplaceable history, and over 20 unique job and company level attributes and identifiers.

-Enhance Alpha. Create models and signals to assess and predict job growth at the macro, sector, geographic, and individual company level

1990 to present (approximate 2 month lag) Virginia Labor Force and Unemployment estimates by Month by County.

Special data considerations: Period values of "M01-M12" represent Months of Year; "M13" is the Annual Average.

U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, table la.data.54.Virginia Data accessed from the Bureau of Labor Statistics public database LABSTAT (https://download.bls.gov/pub/time.series/la/)

Supporting documentation can be found on the U.S. Bureau of Labor Statistics website under Local Area Unemployment Statistics, Handbook of Methods (https://www.bls.gov/opub/hom/lau/home.htm)

Survey Description: Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.

These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.

To establish uniform labor force concepts and definitions in all States and areas consistent with those used for the U.S. as a whole, monthly national estimates of employment and unemployment from the Current Population Survey are used as controls (benchmarks) for the State labor force statistics.

Summary Data Available: Monthly labor force and unemployment series are available for approximately 7,500 geographic areas, including cities over 25,000 population, counties, metropolitan areas, States, and other areas.

For each area, the following measures are presented by place of residence:

• Total civilian labor force,
• Total number of people employed,
• Total number of people unemployed, and
• Unemployment rate

Data Characteristics: Rates are expressed as percents with one decimal place. Levels are measured as individual persons (not thousands) and are stored with no decimal places.

This powerful dataset represents a meticulously curated snapshot of the United States job market throughout 2021, sourced directly from CareerBuilder, a venerable employment website founded in 1995 with a formidable global footprint spanning the US, Canada, Europe, and Asia. It offers an unparalleled opportunity for in-depth research and strategic analysis.

Dataset Specifications:

• Source: CareerBuilder.com (US Listings)
• Crawled by: Crawl Feeds in-house team
• Volume: Over 422,000 unique job records
• Timeliness: Last crawled in May 2021, providing a critical historical benchmark for post-pandemic labor market recovery and shifts.
• Format: Compressed ZIP archive containing structured JSON files, designed for seamless integration into databases, analytical platforms, and machine learning pipelines.
• Accessibility: Published and available immediately for acquisition.

Richness of Detail (22 Comprehensive Fields):

The true analytical power of this dataset stems from its 22 granular data points per job listing, offering a multi-faceted view of each employment opportunity:

1. Core Job & Role Information:

   • id: A unique, immutable identifier for each job posting.
   • title: The specific job role (e.g., "Software Engineer," "Marketing Manager").
   • description: A condensed summary of the role, responsibilities, and key requirements.
   • raw_description: The complete, unformatted HTML/text content of the original job posting – invaluable for advanced Natural Language Processing (NLP) and deeper textual analysis.
   • posted_at: The precise date and time the job was published, enabling trend analysis over daily or weekly periods.
   • employment_type: Clarifies the nature of the role (e.g., "Full-time," "Part-time," "Contract," "Temporary").
   • url: The direct link back to the original job posting on CareerBuilder, allowing for contextual validation or deeper exploration.

2. Compensation & Professional Experience:

   • salary: Numeric ranges or discrete values indicating the compensation offered, crucial for salary benchmarking and compensation strategy.
   • experience: Specifies the level of professional experience required (e.g., "Entry-level," "Mid-senior level," "Executive").

3. Organizational & Sector Context:

   • company: The name of the employer, essential for company-specific analysis, competitive intelligence, and brand reputation studies.
   • domain: Categorizes the job within broader industry sectors or functional areas, facilitating industry-specific talent analysis.

4. Skills & Educational Requirements:

   • skills: A rich collection of keywords, phrases, or structured tags representing the specific technical, soft, or industry-specific skills sought by employers. Ideal for identifying skill gaps and emerging skill demands.
   • education: Outlines the minimum or preferred educational qualifications (e.g., "Bachelor's Degree," "Master's Degree," "High School Diploma").

5. Precise Geographic & Location Data:

   • country: Specifies the country (United States for this dataset).
   • region: The state or province where the job is located.
   • locality: The city or town of the job.
   • address: The specific street address of the workplace (if provided), enabling highly localized analysis.
   • location: A more generalized location string often provided by the job board.
   • postalcode: The exact postal code, allowing for granular geographic clustering and demographic overlay.
   • latitude & longitude: Geospatial coordinates for precise mapping, heatmaps, and proximity analysis.

6. Crawling Metadata:

   • crawled_at: The exact timestamp when each individual record was acquired, vital for understanding data freshness and chronological analysis of changes.

Expanded Use Cases & Analytical Applications:

This comprehensive dataset empowers a wide array of research and commercial applications:

• Deep Labor Market Trend Analysis:

  • Identify the most in-demand job titles, skills, and educational backgrounds across different US regions and industries in 2021.
  • Analyze month-over-month or quarter-over-quarter hiring trends to understand recovery patterns or shifts in specific sectors post-pandemic.
  • Spot emerging job roles or skill combinations that gained prominence during the dataset's period.
  • Assess the volume of remote vs. in-person job postings and their distribution.

• Strategic Talent Acquisition & HR Analytics:

  • Benchmark job requirements, salary ranges, and desired experience levels against market averages for specific roles.
  • Optimize job descriptions by identifying common keywords and phrases used by top employers for similar positions.
  • Understand the competitive landscape for talent in specific geographic areas or specialized skill sets.
  • Develop data-driven recruitment strategies by identifying where and how competitors are hiring.

• Compensation & Benefits Research:

  • Conduct detailed salary analysis broken down by job title, industry, location (state, city, even postal code), experience level, and required skills.
  • Identify potential salary premiums or discrepancies for niche skills or hard-to-fill roles.
  • Support robust compensation planning and negotiation strategies.

• Educational & Workforce Development Planning:

  • Universities and vocational schools can align curriculum with real-world employer demand by analyzing required skills and education fields.
  • Government agencies can identify areas for workforce retraining or development programs based on skill gaps revealed in job postings.
  • Career counselors can advise job seekers on in-demand skills and promising career paths.

• Economic Research & Forecasting:

  • Economists can use the volume and nature of job postings as a leading indicator for economic activity and regional growth.
  • Analyze the impact of economic policies or global events on specific industries' hiring patterns.
  • Study labor mobility and migration patterns based on job locations.

• Competitive Intelligence for Businesses:

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Linkedin was the leading job-related platform in Poland in August 2022, with almost 5.5 million users (website and app). The Pracuj platform followed, with 4.21 million users.

Development of LinkedIn in Poland

LinkedIn is a social media platform mainly used for professional networking and career development. The platform, founded in 2003, allows job seekers to post their resumes and employers to post job opportunities. Half of LinkedIn's Polish users in 2023 were between the ages of 25 and 34. As the popularity of this platform grew, revenue also trended upward, reaching more than 69 thousand U.S. dollars in February 2023.

Poland's labor market

As of early 2023, Poland's unemployment rate stood at 5.9 percent. That rate fell by 0.9 percentage points in July of the same year. With the development of technology, more and more people are looking for jobs online. In 2022, more than 1.1 million job offers were posted on the Polish job search platform Pracuj.pl. There, offers in the retail and IT industries prevailed. The reason why more than half of the Poles were looking for a new job was the expectation of higher wages.

Employment by industry and sex, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

Unemployment Rate in the United States increased to 4.20 percent in July from 4.10 percent in June of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This is a large dataset which contains the labour market statistics data series published in the monthly Labour Market Statistics Statistical Bulletin. The dataset is overwritten every month and it therefore always contains the latest published data. The Time Series dataset facility is primarily designed for users who wish to customise their own datasets. For example, users can create a single spreadsheet including series for unemployment, claimant count, employment and workforce jobs, rather than extracting the required data from several separate spreadsheets published on the website.

The global job search site market is experiencing robust growth, driven by increasing internet penetration, the rise of mobile technology, and a growing preference for online job applications among both employers and job seekers. The market's evolution is marked by a shift towards specialized platforms catering to niche industries and skill sets, as well as an increased emphasis on AI-powered features like personalized job recommendations and applicant tracking systems. While established players like LinkedIn and Indeed maintain significant market share, the competitive landscape remains dynamic, with new entrants and innovative features constantly emerging. The market segmentation reveals a strong preference for cloud-based solutions across all user types (large enterprises, SMEs, and individuals). The North American market currently holds the largest share, fueled by a mature digital economy and a high concentration of tech-driven companies, but significant growth potential exists in Asia Pacific, particularly in India and China, driven by rapid economic expansion and a growing young workforce. The market is also seeing increased demand for features focusing on remote work opportunities and skills-based matching, aligning with broader labor market shifts. The forecast period (2025-2033) anticipates continued expansion, propelled by ongoing technological advancements and a persistent need for efficient recruitment solutions. Factors such as data privacy concerns and the potential for algorithmic bias pose challenges to market growth. However, ongoing innovation in areas such as AI-driven candidate screening and enhanced user experiences is expected to mitigate these concerns and fuel further expansion. Continued investment in improving user experience, personalization, and mobile optimization will be crucial for job search site success in the coming years. The increasing integration of social media platforms and the expanding use of virtual reality (VR) and augmented reality (AR) technologies in the recruitment process also present compelling growth opportunities. Successful companies will be those that adapt swiftly to technological changes and effectively address evolving user needs.

Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by data type (seasonally adjusted and trend-cycle), gender and age group. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

Single-month estimates of employment, unemployment and economic inactivity, UK, rolling three-monthly figures published monthly, seasonally adjusted. Labour Force Survey.

Labour market indicators for Wales including employment, unemployment, economic inactivity, workers' hours, jobs and Claimant Count, rolling three-monthly figures published monthly.

The datasets consist of a corpus of legal sources in the EU legal system mentioning the expression “labour market” (1968 – March 2023). Data were collected from the Eur-Lex website and then coded by hand according to pre-established definitions of “labour market”. The database contains information on the year, subject matter, and institutional author of the legal text, as well as hyperlinks to the original documents.

Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by province, gender and age group. Data are presented for 12 months earlier, previous month and current month, as well as year-over-year and month-to-month level change and percentage change. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.