Discover the "Job.com USA Jobs Dataset," a detailed resource that provides an in-depth look at the job market in the United States.

This dataset is sourced from Job.com, a leading employment platform in the USA, and includes comprehensive information on job listings across various industries and regions.

Key Features:

• Extensive Job Listings: Features a wide range of job postings from different sectors and industries, offering a comprehensive overview of employment opportunities across the United States.
• Detailed Information: Each listing includes important details such as job titles, company names, job descriptions, locations, employment types (full-time, part-time, remote, contract), required qualifications, and salary data.
• Insights into Market Trends: Analyze current trends in the US job market, including in-demand skills, leading employers, popular job roles, and geographic distribution of job opportunities.
• Ideal for Research and Analysis: This dataset is perfect for researchers, HR professionals, and data analysts interested in studying labor market trends, developing recruitment strategies, or understanding the employment dynamics in the USA.

The Job.com USA Jobs Dataset offers valuable insights into the American job market, making it a crucial resource for job seekers, employers, and researchers alike. Use this dataset to stay ahead of market trends, explore employment opportunities, and gain a deeper understanding of job market dynamics in the United States.

Job Growth Statistics: Statistics on job growth are essential in understanding the state and trajectory of an economy because they offer insight into the shifting dynamics of labor markets. By measuring net job addition or subtraction over a certain timeframe, employment growth statistics allow policymakers, companies, and individuals to make well-informed decisions regarding workforce planning, investment decisions, or career choices. Statistics on job growth provide a key measure of economic development as they show whether an economy is expanding, contracting, or remaining stable. Positive employment growth numbers often signal healthy economies with increased consumer spending and company confidence. Conversely, negative or stagnant job growth indicates a slowdown or recession. Furthermore, statistics on employment growth may also be used to highlight developing markets and professions for policymakers as well as job seekers in finding prospective development areas. As such, employment data provides an essential means of measuring an economy's current state and future direction, as well as helping shape policies and initiatives within it. Editor’s Choice From 2020-2030; job growth in the US is anticipated to be 5.3%. Nurse practitioners are predicted to experience the highest job growth; between 2021-2031 at 45.7%; 2019 alone saw sectors producing goods create 188,000 new jobs. Leisure and hospitality job creation decreased by 47% year-on-year between April 2020 and March 2021. President Clinton created 19 million new employment opportunities between June and July of 2022 and 528,000 nonfarm payroll employees were gained; yet by April 2020 20.5 million jobs had been lost from the economy as a whole. By 2031, it is projected that employment opportunities across the nation will reach 166.5 million; over that same timeframe childcare service workers have seen their ranks decline by 336,000. Since the COVID-19 outbreak, healthcare employment levels have suffered a dramatic decrease. By some accounts, over one and a half million employees may have left healthcare jobs since 2016. (Source: zippia.com)

Job Dataset

This dataset provides a comprehensive collection of synthetic job postings to facilitate research and analysis in the field of job market trends, natural language processing (NLP), and machine learning. Created for educational and research purposes, this dataset offers a diverse set of job listings across various industries and job types.

Descriptions for each of the columns in the dataset:

1. Job Id: A unique identifier for each job posting.
2. Experience: The required or preferred years of experience for the job.
3. Qualifications: The educational qualifications needed for the job.
4. Salary Range: The range of salaries or compensation offered for the position.
5. Location: The city or area where the job is located.
6. Country: The country where the job is located.
7. Latitude: The latitude coordinate of the job location.
8. Longitude: The longitude coordinate of the job location.
9. Work Type: The type of employment (e.g., full-time, part-time, contract).
10. Company Size: The approximate size or scale of the hiring company.
11. Job Posting Date: The date when the job posting was made public.
12. Preference: Special preferences or requirements for applicants (e.g., Only Male or Only Female, or Both)
13. Contact Person: The name of the contact person or recruiter for the job.
14. Contact: Contact information for job inquiries.
15. Job Title: The job title or position being advertised.
16. Role: The role or category of the job (e.g., software developer, marketing manager).
17. Job Portal: The platform or website where the job was posted.
18. Job Description: A detailed description of the job responsibilities and requirements.
19. Benefits: Information about benefits offered with the job (e.g., health insurance, retirement plans).
20. Skills: The skills or qualifications required for the job.
21. Responsibilities: Specific responsibilities and duties associated with the job.
22. Company Name: The name of the hiring company.
23. Company Profile: A brief overview of the company's background and mission.

Potential Use Cases:

• Building predictive models to forecast job market trends.
• Enhancing job recommendation systems for job seekers.
• Developing NLP models for resume parsing and job matching.
• Analyzing regional job market disparities and opportunities.
• Exploring salary prediction models for various job roles.

Acknowledgements:

We would like to express our gratitude to the Python Faker library for its invaluable contribution to the dataset generation process. Additionally, we appreciate the guidance provided by ChatGPT in fine-tuning the dataset, ensuring its quality, and adhering to ethical standards.

Note:

Please note that the examples provided are fictional and for illustrative purposes. You can tailor the descriptions and examples to match the specifics of your dataset. It is not suitable for real-world applications and should only be used within the scope of research and experimentation. You can also reach me via email at: rrana157@gmail.com

Introduction

The Job Market Insights Dataset offers a comprehensive view of job postings worldwide, providing critical data on job roles, salaries, qualifications, locations, and company profiles. This dataset serves as a valuable resource for understanding global employment trends and patterns in various industries.

Objective

The primary objective of analyzing this dataset is to gain actionable insights into job market dynamics, including in-demand skills, salary ranges by role, preferred qualifications, and geographical job distributions. This analysis can empower job seekers, recruiters, and businesses to make informed decisions.

Key Features

1. Diverse Job Roles: Includes details for various professions like Network Engineers, Software Testers, UX/UI Designers, and more.
2. Global Scope: Covers jobs from diverse locations, spanning countries and industries worldwide.
3. Comprehensive Data Points: Provides salary ranges, qualifications, job types, company profiles, and benefits offered.
4. Temporal Data: Captures job posting dates to understand trends over time.
5. Skills and Responsibilities: Details required skills and responsibilities, aiding in understanding role-specific requirements.

Benefits for Data Science

• Predictive Modeling: Build models to predict salaries, skill demands, or the probability of job fulfillment.
• Trend Analysis: Identify trends in job roles, qualifications, and compensation.
• Geospatial Analysis: Map job distributions to uncover opportunities in specific regions.
• Clustering & Segmentation: Segment jobs by industry, role, or qualifications for targeted insights.
• Skill Gap Identification: Analyze skill requirements to identify gaps between current offerings and market demands.

This dataset is a goldmine for extracting insights that can optimize recruitment strategies, guide career planning, and inform educational initiatives.

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.

Job Trends in Australia

Insight into Job Types, Salaries and Growth Across States

By [source]

About this dataset

This dataset provides an insightful look into the Australian job market and the country's current trend of economic development. It consists of 30000 unique job postings from SEEK Australia, a renowned job board in Australia, offering valuable insights regarding salaries, job types, and openings across cities and states.

The data allows researchers to compare which type of jobs are offered across different locations, providing critical information on which cities or states offer particular kinds of jobs. Moreover, it offers a framework that can be used to understand how different companies compare when it comes to salaries and hiring practices. In addition, this dataset provides an in-depth view into what type of job openings there are in each city or state and their respective salaries. All this is available through reliable columns such as city, state, company name, salary offered & url enabling effective analysis and providing consumers with much needed knowledge about their potential employment opportunities in the market

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How to use the dataset

This dataset can be used to gain insights into the Australian job market – from job types, salaries, and locations to trends in growth across states. To get started working with this data, you will need to download the dataset from Kaggle.

Once you have the dataset downloaded, it is important to become familiar with the different fields available as these will influence what kind of analysis you can do. The columns include category, city, company name, geo coordinates (for location-based analysis), job board (to determine where these jobs were posted), job description (to find relevant keywords and topics related with each position), job title (to search for specific jobs or trends in titles over time), job type (i.e full time/part-time etc.), posting date and salary offered.

You can further filter your results based on any combination of these different column values to get more targeted information about a certain area or topic that you are researching on. Additionally, visualizing certain elements such as salary ranges by region/job type may be helpful for gaining a wide understanding of Australia’s labor landscape in various sectors and cities.

Finally, it may also be useful to look at how salaries might have changed over time by comparing postings from 2 different years for example which could help identify employment growth areas or opportunities for businesses looking to set up shop in certain regions etc

Research Ideas

• Analyzing Salary Trends: By investigating the salaries of various job postings, researchers can gain insights on wage growth and wage disparities across different cities and states in Australia.
• Comparing Job Types & Salaries: Researchers can observe which cities offer higher salaries for particular job types and also get an understanding of what is expected from potential applicants.
• Tracking Job Market Growth: By using data from the years before, it is possible to identify which areas have seen the most growth in terms of job opportunities and how that compares with other areas in Australia

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: seek_australia.csv | Column name | Description | |:--------------------|:------------------------------------------------------------| | category | The category of the job posting. (String) | | city | The city in which the job is located. (String) | | company_name | The name of the company offering the job. (String) | | geo | The geographic coordinates of the job location. (String) | | job_board | The job board on which the job was posted. (String) | | job_description | The description of the job. (String) | | job_title | The title of the job. (...

In the 3rd quarter of 2025, the employment rate in the United Kingdom was 75 percent, down from 75.3 percent in the previous quarter. After almost dropping to 70.1 percent in 2011, the employment rate in the United Kingdom started to climb at a relatively fast pace, peaking in early 2020. Due to the onset of the COVID-19 pandemic, however, employment declined to 74.6 percent by January 2021. Although not quite at pre-pandemic levels, the employment rate has since recovered. Labor market trouble in 2025? Although unemployment in the UK spiked at 5.3 percent in the aftermath of the COVID-19 pandemic, it fell throughout most of 2022, to just 3.6 percent in August 2022. Around that time, the number of job vacancies in the UK was also at quite high levels, reaching a peak of 1.3 million by May 2022. The strong labor market put employees in quite a strong position, perhaps encouraging the high number of resignations that took place around that time. Since 2023, however, the previously hot labor market has cooled, with unemployment reaching 4.6 percent in April 2025 and job vacancies falling to a four-year low of 736,000 in May 2025. Furthermore, the number of employees on UK payrolls has fallen by 227,500 in the first five months of the year, indicating that 2025 will be a tough one for the labor market. Headline economic measures revised in early 2025 Along with the unemployment rate, the UK's inflation rate is also expected to be higher than initially thought in 2025, reaching a rate of 3.2 percent for the year. The economy will also grow at a slower pace of one percent rather than the initial prediction of two percent. Though these negative trends are not expected to continue in the long term, the current government has already expended significant political capital on unpopular decisions, such as the cutting of Winter Fuel Payments to pensioners in 2024. As of June 2025, they are almost as unpopular as the previous government, with a net approval rating of -52 percent.

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 2025, it was estimated that over 163 million Americans were in some form of employment, while 4.16 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.

We examine current conditions in the labor market and trends affecting its workers, as well as topics related to healthy labor markets, such as education.

This dataset provides values for LABOR MARKET CONDITIONS INDEX reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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

This dataset provides insights into the United States job market by presenting a detailed breakdown of job posting titles, associated skill keywords, and their respective counts. It can be used for:

• Labor Market Analysis: Understand current trends in job roles and required skills.
• Career Planning: Identify in-demand skills for professional development.
• Recruitment Strategies: Optimize job descriptions and target relevant skills.
• Educational Curriculum Development: Align educational programs with industry needs.

The dataset includes the following columns:

• Job Posting Title: The title of the job posting (e.g., 'Software Engineer', 'Data Scientist').
• Skill Keyword: A specific skill identified within the job posting (e.g., 'Python', 'SQL', 'Machine Learning').
• Count: The frequency or occurrence of the Skill Keyword for the given Job Posting Title.

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector.This public use microdata file contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). It contains both personal characteristics for all individuals in the household and detailed labour force characteristics for household members 15 years of age and over. The personal characteristics include age, sex, marital status, educational attainment, and family characteristics. Detailed labour force characteristics include employment information such as class of worker, usual and actual hours of work, employee hourly and weekly wages, industry and occupation of current or most recent job, public and private sector, union status, paid or unpaid overtime hours, job permanency, hours of work lost, job tenure, and unemployment information such as duration of unemployment, methods of job search and type of job sought. Labour force characteristics are also available for students during the school year and during the summer months as well as school attendance whether full or part-time and the type of institution.LFS revisions: Labour force surveys are revised on a periodic basis, either to adopt the most recent geography, industry and occupation classifications; to use new observations to fine-tune seasonal adjustment factors; or to introduce methodological enhancement. Prior LFS revisions were conducted in 2011, 2015 and 2021. The most recent revisions to the LFS were conducted in 2023. The first major change was a transition to the National Occupational Classification (NOC) 2021 V1.0, with all LFS series from 1987 onwards having been revised to the new classification. The second major change were methodological enhancements to LFS data processing, applied to all LFS series beginning Jan 2006. The third major change was a revision of seasonal adjustment factors, applied to LFS series Jan 2002 onward. A list of prior versions of this LFS dataset can be found under the ‘Versions’ tab.

This publication provides the most current monthly labour market statistics. Each month, this publication contains a brief commentary highlighting recent developments in the Canadian labour market. It also includes a series of charts and tables on a variety of labour force characteristics, such as employment and unemployment for Canada, the provinces, metropolitan areas and economic regions.

This dataset presents the change in employment through a projection of employment by industries for metropolitan areas following the Greater Capital City Statistical Area (GCCSA) regions projected from 2019 to May 2024. The boundaries for this dataset follow the 2016 edition of the Australian Statistical Geography Standard (ASGS).

The Australian Department of Education, Skills and Employment publishes a range of labour market data on its Labour Market Information Portal. The data provided includes unemployment rate, employment rate, participation rate, youth unemployment rate, unemployment duration, population by age group and employment by industry and occupation.

Each year, the National Skills Commission produces employment projections by industry, occupation, skill level and region for the following five-year period. These employment projections are designed to provide a guide to the future direction of the labour market, however, like all such exercises, they are subject to an inherent degree of uncertainty.

The 2019 employment projections are based on the forecasted and projected total employment growth rates published in the 2019-20 Budget, the Labour Force Survey (LFS) data (June 2019) for total employment, and the quarterly detailed LFS data (May 2019) for industry employment data.

AURIN has spatially enabled the original data. Data Source: Department of Jobs and Small Business 2019 Employment Projections, Five Years to May 2024. The 2019 employment projections do not take account of any impact caused by the COVID-19 pandemic and are therefore no longer reflective of current labour market conditions. As such, they should be used, and interpreted, with extreme caution..

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.

View monthly updates and historical trends for US Labor Force Participation Rate. from United States. Source: Bureau of Labor Statistics. Track economic d…

Techsalerator’s Job Openings Data in Africa offers a comprehensive and insightful dataset designed to provide businesses, recruiters, labor market analysts, and job seekers with a thorough view of employment opportunities across the African continent. This dataset aggregates job postings from a wide range of sources on a daily basis, ensuring that users have access to the most current and extensive collection of job openings available throughout Africa.

Key Features of the Dataset: Broad Coverage:

The dataset aggregates job postings from numerous sources including company career pages, job boards, recruitment agencies, and professional networking sites. This extensive coverage ensures a broad spectrum of job opportunities from multiple channels. Daily Updates:

Job posting data is updated daily, providing real-time insights into the job market. This frequent updating ensures that the dataset reflects the latest job openings and market trends. Sector-Specific Data:

Job postings are categorized by industry sectors such as technology, healthcare, finance, education, manufacturing, and more. This categorization allows users to analyze trends and opportunities within specific industries. Regional Breakdown:

The dataset includes detailed information on job openings across different countries and regions within Africa. This regional breakdown helps users understand job market dynamics and opportunities in various geographic locations. Role and Skill Insights:

The dataset includes information on job roles, required skills, qualifications, and experience levels. This feature assists job seekers in finding opportunities that match their expertise and helps recruiters identify candidates with the desired skill sets. Company Information:

Users can access details about the companies posting job openings, including company names, industries, and locations. This data provides insights into which companies are hiring and where the demand for talent is highest. Historical Data:

The dataset may include historical job posting data, enabling users to perform trend analysis and comparative studies over time. This feature supports understanding changes and developments in the job market. African Countries Covered: Northern Africa: Algeria Egypt Libya Mauritania Morocco Sudan Tunisia Sub-Saharan Africa: West Africa: Benin Burkina Faso Cape Verde Ivory Coast (Côte d'Ivoire) Gambia Ghana Guinea Guinea-Bissau Liberia Mali Niger Nigeria Senegal Sierra Leone Togo Central Africa: Angola Cameroon Central African Republic Chad Congo, Republic of the Congo, Democratic Republic of the Equatorial Guinea Gabon São Tomé and Príncipe East Africa: Burundi Comoros Djibouti Eritrea Eswatini (Swaziland) Ethiopia Kenya Lesotho Malawi Mauritius Rwanda Seychelles Somalia Tanzania Uganda Southern Africa: Botswana Lesotho Namibia South Africa Swaziland (Eswatini) Zimbabwe Benefits of the Dataset: Enhanced Recruitment Strategies: Recruiters and HR professionals can use the dataset to identify hiring trends, understand competitive practices, and refine recruitment strategies based on real-time market insights. Labor Market Analysis: Analysts and policymakers can leverage the dataset to study employment trends, identify skill gaps, and evaluate job market opportunities across different regions and sectors. Job Seeker Support: Job seekers can access a comprehensive and updated list of job openings tailored to their skills and preferred locations, making their job search more efficient and targeted. Strategic Workforce Planning: Companies can gain valuable insights into the availability of talent across Africa, assisting with decisions related to market expansion, office locations, and talent acquisition. Techsalerator’s Job Openings Data in Africa is a critical resource for understanding the diverse and evolving job markets across the continent. By providing up-to-date and detailed information on job postings, it supports effective decision-making for businesses, job seekers, and labor market analysts.