Explore the "CareerBuilder US Jobs Dataset – August 2021," a valuable resource for understanding the dynamics of the American job market.

This dataset features detailed job listings from CareerBuilder, one of the largest employment websites in the United States, and provides a comprehensive snapshot of job postings as of August 2021.

Key Features:

• Extensive Job Listings: Includes thousands of job postings across various industries and sectors, providing a broad view of employment opportunities in the US.
• Detailed Information: Each listing contains essential details such as job titles, company names, locations, job descriptions, employment types (full-time, part-time, contract), required qualifications, and salary ranges.
• Insights into Trends: Analyze trends in employment, including the most in-demand skills, top hiring companies, popular job roles, and geographic distribution of job opportunities.
• Ideal for Research: This dataset is perfect for researchers, HR professionals, and data analysts interested in understanding the current state of the job market, developing recruitment strategies, or studying labor market dynamics.

By leveraging this dataset, you can gain valuable insights into the US job market as of August 2021, helping you stay ahead of industry trends and make informed decisions. Whether you're a job seeker, employer, or researcher, the CareerBuilder US Jobs Dataset offers a wealth of information to explore.

In 2023, it was estimated that over 161 million Americans were in some form of employment, while 3.64 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

Employment Rate in the United States remained unchanged at 59.70 percent in June. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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

Unemployment Rate in the United States decreased to 4.10 percent in June from 4.20 percent in May 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.

Job Offers in the United States increased to 7769 Thousand in May from 7395 Thousand in April of 2025. This dataset provides the latest reported value for - United States Job Openings - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

By the last business day of September 2024, there were about 7.44 million job openings in the United States. This is a decrease from the previous month, when there were 7.86 million job openings. The data are seasonally adjusted. Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends.

The Job Openings and Labor Turnover Survey (JOLTS) program provides national estimates of rates and levels for job openings, hires, and total separations. Total separations are further broken out into quits, layoffs and discharges, and other separations. Unadjusted counts and rates of all data elements are published by supersector and select sector based on the North American Industry Classification System (NAICS). The number of unfilled jobs—used to calculate the job openings rate—is an important measure of the unmet demand for labor. With that statistic, it is possible to paint a more complete picture of the U.S. labor market than by looking solely at the unemployment rate, a measure of the excess supply of labor. Information on labor turnover is valuable in the proper analysis and interpretation of labor market developments and as a complement to the unemployment rate. For more information and data visit: https://www.bls.gov/jlt/

📂 Dataset Title:

AI Impact on Job Market: Increasing vs Decreasing Jobs (2024–2030)

📝 Dataset Description:

This dataset explores how Artificial Intelligence (AI) is transforming the global job market. With a focus on identifying which jobs are increasing or decreasing due to AI adoption, this dataset provides insights into job trends, automation risks, education requirements, gender diversity, and other workforce-related factors across industries and countries.

The dataset contains 30,000 rows and 13 valuable columns, generated to reflect realistic labor market patterns based on ongoing research and public data insights. It can be used for data analysis, predictive modeling, AI policy planning, job recommendation systems, and economic forecasting.

📊 Columns Description:

Column Name Description

Job Title Name of the job/role (e.g., Data Analyst, Cashier, etc.) Industry Industry sector in which the job is categorized (e.g., IT, Healthcare, Manufacturing) Job Status Indicates whether the job is Increasing or Decreasing due to AI adoption AI Impact Level Estimated level of AI impact on the job: Low, Moderate, or High Median Salary (USD) Median annual salary for the job in USD Required Education Typical minimum education level required for the job Experience Required (Years) Average number of years of experience required Job Openings (2024) Number of current job openings in 2024 Projected Openings (2030) Projected job openings by the year 2030 Remote Work Ratio (%) Estimated percentage of jobs that can be done remotely Automation Risk (%) Probability of the job being automated or replaced by AI Location Country where the job data is based (e.g., USA, India, UK, etc.) Gender Diversity (%) Approximate percentage representation of non-male genders in the job

🔍 Potential Use Cases:

Predict which jobs are most at risk due to automation.

Compare AI impact across industries and countries.

Build dashboards on workforce diversity and trends.

Forecast job market shifts by 2030.

Train ML models to predict job growth or decline.

📚 Source:

This is a synthetic dataset generated using realistic modeling, public job data patterns (U.S. BLS, OECD, McKinsey, WEF reports), and AI simulation to reflect plausible scenarios from 2024 to 2030. Ideal for educational, research, and AI project purposes.

📌 License: MIT

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. Revenue generated from online recruitment sites is expected to grow at a CAGR of 8.3% to $15.7 billion over the five years to 2023. While growth has been fueled by an extremely tight labor market following pandemic disruptions, revenue is forecast to contract 4.6% in 2023. Low costs associated with starting an online company have encouraged new companies to begin operations online. The largest online recruitment sites have increased market share through organic growth and via the acquisition of smaller players, which have targeted niche industries. Incumbents hold a competitive advantage in developing brand names, which has made it difficult for new sites to gain market share. Nonetheless, low barriers to entry and strength in demand for professional and technical recruiting have enabled some niche job boards to succeed within their respective markets. The growing advantages associated with using online recruitment sites and the scalability of online platforms enable sizable profit margins. Online hiring played an integral role across the economy during the COVID-19 pandemic, as employers have also to interact with customers and employees in new ways. Driven by the rapid development and adoption of big data analytics and mobile computing, online recruitments sites are expected to provide a broader range of services that go beyond standard job posting services and resume collection. These services will enable online recruiters to compete more effectively with traditional recruiting companies and in-house hiring departments. Meanwhile, a steady labor market will likely create new job openings even as interest rates rise, particularly in small- and medium-sized businesses. Revenue across online recruitment sites is forecast to grow at a CAGR of 4.4% to $19.5 billion over the five years to 2028.

Graph and download economic data for Job Openings: Total Nonfarm (JTSJOL) from Dec 2000 to May 2025 about job openings, vacancy, nonfarm, and USA.

In 2024, the education and health services industry employed the largest number of people in the United States. That year, about 37 million people were employed in the education and health services industry. Education and Health Services Industry Despite being one of the wealthiest nations in the world, the United States has started to fall behind in both education and the health care industry. Although the U.S. spends the most money in both these industries, they do not see their desired results in comparison to other nations. Furthermore, in the education services industry, there was a relatively significant wage gap between men and women. In 2019, men earned about 1,070 U.S. dollars per week on average, while their female counterparts only earned 773 U.S. dollars per week. Employment in the U.S. The 2008 financial crisis was a large-scale event that impacted the entire world, especially the United States. The economy started to improve after 2010, and the number of people employed in the United States has been steadily increasing since then. However, the number of people employed in the education sector is expected to slowly decrease until 2026. The overall unemployment rate in the United States has decreased since 2010 as well.

📊 Job Postings Data for Talent Acquisition, HR Strategy & Market Research Canaria’s Job Postings Data product is a structured, AI-enriched dataset that captures and organizes millions of job listings from leading sources such as Indeed, LinkedIn, and other recruiting platforms. Designed for decision-makers in HR, strategy, and research, this data reveals workforce demand trends, employer activity, and hiring signals across the U.S. labor market and enhanced with advanced enrichment models.

The dataset enables clients to track who is hiring, what roles are being posted, which skills are in demand, where talent is needed geographically, and how compensation and employment structures evolve over time. With field-level normalization and deep enrichment, it transforms noisy job listings into high-resolution labor intelligence—optimized for strategic planning, analytics, and recruiting effectiveness.

🧠 Use Cases: What This Job Postings Data Solves This enriched dataset empowers users to analyze workforce activity, employer behavior, and hiring trends across sectors, geographies, and job categories.

🔍 Talent Acquisition & HR Strategy • Identify hiring trends by industry, company, function, and geography • Optimize job listings and outreach with enriched skill, title, and seniority data • Detect companies expanding or shifting their workforce focus • Monitor new roles and emerging skills in real time

📈 Labor Market Research & Workforce Planning • Visualize job market activity across cities, states, and ZIP codes • Analyze hiring velocity and job volume changes as macroeconomic signals • Correlate job demand with company size, sector, or compensation structure • Study occupational dynamics using AI-normalized job titles • Use directional signals (job increases/declines) to anticipate market shifts

📊 HR Analytics & Compensation Intelligence • Map salary ranges and benefits offerings by role, location, and level • Track high-demand or hard-to-fill positions for strategic workforce planning • Support compensation planning and headcount forecasting • Feed job title normalization and metadata into internal HRIS systems • Identify talent clusters and location-based hiring inefficiencies

🌐 What Makes This Job Postings Data Unique

🧠 AI-Based Enrichment at Scale • Extracted attributes include hard skills, soft skills, certifications, and education requirements • Modeled predictions for seniority level, employment type, and remote/on-site classification • Normalized job titles using an internal taxonomy of over 50,000 unique roles • Field-level tagging ensures structured, filterable, and clean outputs

💰 Salary Parsing & Compensation Insights • Parsed salary ranges directly from job descriptions • AI-based salary predictions for postings without explicit compensation • Compensation patterns available by job title, company, and location

🔁 Deduplication & Normalization • Achieves approximately 60% deduplication rate through semantic and metadata matching • Normalizes company names, job titles, location formats, and employment attributes • Ready-to-use, analysis-grade dataset—fully structured and cleansed

🔗 Company Matching & Metadata • Each job post is linked to a structured company profile, including metadata • Records are cross-referenced with LinkedIn and Google Maps to validate company identity and geography • Enables aggregation at employer or location level for deeper insights

🕒 Freshness & Scalability • Updated hourly to reflect real-time hiring behavior and job market shifts • Delivered in flexible formats (CSV, JSON, or data feed) and customizable filters • Supports segmentation by geography, company, seniority, salary, title, and more

🎯 Who Uses Canaria’s Job Postings Data • HR & Talent Teams – to benchmark roles, optimize pipelines, and compete for talent • Consultants & Strategy Teams – to guide clients with labor-driven insights • Market Researchers – to understand employment dynamics and job creation trends • HR Tech & SaaS Platforms – to power salary tools, job market dashboards, or recruiting features • Economic Analysts & Think Tanks – to model labor activity and hiring-based economic trends • BI & Analytics Teams – to build dashboards that track demand, skill shifts, and geographic patterns

📌 Summary Canaria’s Job Postings Data provides an AI-enriched, clean, and analysis-ready view of the U.S. job market. Covering millions of listings from Indeed, LinkedIn, other job boards, and ATS sources, it includes detailed job attributes, inferred compensation, normalized titles, skill extraction, and employer metadata—all updated hourly and fully structured.

With deep enrichment, reliable deduplication, and company matchability, this dataset is purpose-built for users needing workforce insights, market trends, and strategic talent intelligence. Whether you're modeling skill gaps, benchmarking compensation, or visualizing hiring momentum, this dataset provides a complete toolkit for HR and labor intellig...

Graph and download economic data for Software Development Job Postings on Indeed in the United States (IHLIDXUSTPSOFTDEVE) from 2020-02-01 to 2025-07-18 about software, jobs, and USA.

As of May 2023, the monthly average number of information sector job openings stood at *** thousand. Notably, there were fewer job openings in the U.S. information sector in 2020 than in the previous years. This is could be attributed due to the outbreak of the COVID-19 pandemic when companies laid off many off their employees and fewer employees were hired generally. In 2022, the job market seemed to have experienced a slight rebound with more IT job openings in the U.S. than in previous years, with around *** thousand job openings monthly on average in 2022.

We offer a unified analysis of the growth of low-skill service occupations between 1980 and 2005 and the concurrent polarization of US employment and wages. We hypothesize that polarization stems from the interaction between consumer preferences, which favor variety over specialization, and the falling cost of automating routine, codifiable job tasks. Applying a spatial equilibrium model, we corroborate four implications of this hypothesis. Local labor markets that specialized in routine tasks differentially adopted information technology, reallocated low-skill labor into service occupations (employment polarization), experienced earnings growth at the tails of the distribution (wage polarization), and received inflows of skilled labor.

Xverum’s Global Job Market & Job Postings Data offers one of the largest datasets available, featuring 280B+ records updated daily. Covering 13M+ daily job postings, employee insights, and recruiting trends, our dataset provides a comprehensive view of global labor market dynamics. Designed to empower workforce analytics, talent acquisition, economic forecasting, and AI & ML model training, it’s an essential resource for data-driven decision-making.

Key Features:

1️⃣ Extensive Job Postings Data: Access 13M+ job postings daily from multiple industries and geographies. Detailed attributes include job titles, descriptions, locations, industries, and application requirements.

2️⃣ Real-Time Updates: Data refreshed daily ensures relevance and accuracy for live applications.

3️⃣ Global Coverage: One of the most extensive datasets available, with hiring activity tracked in every country worldwide.

4️⃣ GDPR-Compliant and Secure: Fully compliant with GDPR and CCPA regulations, ensuring ethical and safe data usage.

Primary Use Cases:

✳️ Workforce Analytics: Monitor job demand and labor market trends for strategic workforce planning.

✳️ Talent Acquisition and Recruiting: Analyze hiring activity to identify recruiting trends and optimize talent strategies.

✳️ Economic Forecasting: Use job postings data as an economic indicator to track industry growth and market opportunities.

✳️ Market Research: Gain insights into hiring activity across industries and regions to understand market dynamics.

✳️ Competitive Intelligence: Track competitor hiring patterns and job postings to benchmark market positioning.

✳️ AI/ML Model Training: Train predictive models for job matching, labor trend forecasting, and workforce optimization.

Why Choose Xverum’s Job Market Data? ✅ Massive Scale: 13M+ daily job postings and 280B+ records ensure unparalleled depth and global reach. ✅ Real-Time Updates: Daily refreshes ensure the latest job data for actionable insights. ✅ Comprehensive Coverage: Spanning industries, and geographies worldwide. ✅ GDPR-Compliant: Secure and ethically sourced data for peace of mind.

Key Data Attributes: 📎 Job title, description, and location. 📎 Industry classification and hiring organization. 📎 Posting date, application deadline, and employment type (e.g., full-time, remote).

Request a sample dataset today or contact us to tailor your job market data solution. Empower your business with Xverum’s Job Market & Job Postings Data for smarter, data-driven decision-making.

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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This graph shows the civilian labor force in the United States from 1990 to 2024. In 2024, the number of people who had jobs or were seeking employment amounted to about 168.11 million.

In 2020, the United States tech sector employed roughly *** million workers, with software developers and software QA the largest occupation with *** million workers. By 2030, the number of employed U.S. tech workers is forecast to reach almost * million.