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.

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.

Techsalerator’s Job Openings Data in Latin America provides a thorough and insightful dataset designed to deliver businesses, recruiters, labor market analysts, and job seekers with a comprehensive view of employment opportunities across the Latin American region. This dataset aggregates job postings from a diverse array of sources on a daily basis, ensuring that users have access to the most current and extensive collection of job openings available throughout Latin America.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates job postings from a variety of sources, including company career sites, job boards, recruitment agencies, and professional networking platforms. This comprehensive coverage ensures that users receive a broad spectrum of job opportunities from multiple channels. Daily Updates:

Data is updated daily, providing real-time insights into job market conditions. 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 segmentation allows users to analyze trends and opportunities within specific industries. Regional Breakdown:

Detailed information is provided on job openings across different countries and key regions within Latin America. This regional breakdown helps users understand job market dynamics and opportunities in various geographic areas. Role and Skill Analysis:

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

Users can access information about the companies posting job openings, including company names, industries, and locations. This data provides insights into which companies are hiring and where 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. Latin American Countries Covered: South America: Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Central America: Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Caribbean: Cuba Dominican Republic Haiti (Note: Primarily French-speaking, but included due to geographic and cultural ties) Jamaica Trinidad and Tobago Benefits of the Dataset: Strategic Recruitment: Recruiters and HR professionals can use the data to identify hiring trends, understand competitive practices, and optimize their 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, enhancing the efficiency and effectiveness of their job search. Workforce Planning: Companies can gain valuable insights into the availability of talent across Latin America, assisting with decisions related to market entry, expansion, and talent acquisition. Techsalerator’s Job Openings Data in Latin America is an essential tool for understanding the diverse and evolving job markets across the region. By providing up-to-date and detailed information on job postings, it supports effective decision-making for businesses, job seekers, and labor market analysts.

Between 2023 and 2027, the majority of companies surveyed worldwide expect big data to have a more positive than negative impact on the global job market and employment, with 65 percent of the companies reporting the technology will create jobs and 7 percent expecting the technology to displace jobs. Meanwhile, artificial intelligence (AI) is expected to result in more significant labor market disruptions, with 23 percent of organizations expecting the technology to displace jobs and 49 percent expecting AI to create jobs.

Explore the Employment Services Market trends! Covers key players, growth rate 10.7% CAGR, market size $3237.5 Billion, and forecasts to 2034. Get insights now!

Following a survey on the impact of artificial intelligence (AI) in the labor market among South Koreans in 2024, 73 percent of respondents answered that there will be more job losses after the implementation of AI. Meanwhile, about 12 percent thought that there will be more jobs in the future.

Forecast: Employment in Advertising and Market Research Sector in Norway 2024 - 2028 Discover more data with ReportLinker!

Job Board Software Market size was valued at USD 504.52 Million in 2024 and is projected to reach USD 875.98 Million by 2031, growing at a CAGR of 7.14% from 2024 to 2031.

Job Board Software Market Drivers

Increase in Online Recruitment: The shift towards online recruitment processes has significantly increased the demand for job board software. Employers and job seekers prefer online platforms for their ease of use, reach, and efficiency.

Rise of the Gig Economy: The growing gig economy and the increasing number of freelance and contract workers drive the need for specialized job board software. These platforms help match freelancers with suitable gigs and projects.

Technological Advancements: Innovations in artificial intelligence (AI), machine learning (ML), and data analytics enhance job board software capabilities. Features like AI-driven matching, automated resume screening, and predictive analytics improve the recruitment process.

Mobile Accessibility: The proliferation of smartphones and mobile internet usage has led to increased demand for mobile-friendly job board software. Users expect seamless access to job listings and application processes via mobile devices.

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.

Temporary Labor Market size was valued at USD 537.37 Billion in 2024 and is projected to reach USD 881.36 Billion by 2031, growing at a CAGR of 6.38% from 2024 to 2031.

The Temporary Labor Market is driven by the growing need for workforce flexibility, as companies seek to quickly adjust staffing in response to demand fluctuations. With economic uncertainties and seasonal shifts in industries like retail, manufacturing, and logistics, temporary labor provides a cost-effective solution to meet changing workforce requirements without long-term commitments. Additionally, the rise of the gig economy and changing workforce preferences are fueling demand, as more workers opt for flexible, short-term employment over traditional roles. Technological advancements in digital staffing platforms also streamline the hiring process, making it easier for employers to access skilled temporary workers on demand, further driving market growth.

Job Postings Dataset

This dataset offers an extensive assortment of job postings, designed to support investigations and examinations within the realms of job market patterns, natural language processing (NLP), and machine learning. Developed for educational and research objectives, this dataset presents a varied array of job advertisements spanning diverse industries and job categories.

Description of each column:

Category- The category of the job. Workplace- If the job in remote, on-site or hybrid. Location- Location of the job posting. Department- The department for which the job has been posted. Type- If the job is full-time, part-time or contractual in nature.

Potential use cases:

1. Optimizing workforce planning and talent acquisition strategies.
2. Developing NLP models for resume parsing and job matching.
3. Building predictive models to forecast job market trends.
4. Exploring salary prediction models for various job roles.
5. Analyzing regional job market disparities and opportunities.

The global job search site market is projected to reach a valuation of million by 2033, exhibiting a CAGR of XX% during the forecast period of 2025-2033. The market growth is attributed to the increasing adoption of cloud-based and web-based job search platforms, rising demand for skilled professionals, and the growing popularity of remote work. The market is segmented based on type (cloud-based, web-based) and application (large enterprises, SMEs, individuals). Cloud-based job search platforms are gaining traction due to their scalability, flexibility, and cost-effectiveness. Large enterprises are the primary users of these platforms, as they offer features such as candidate management, automated screening, and data analytics. Individuals are also increasingly using job search platforms to find suitable job opportunities, leading to the growth of the SME and individual segments. Key players in the market include LinkedIn, Indeed, ZipRecruiter, Hired, Monster, and Glassdoor. Regional analysis reveals that North America and Europe dominate the market due to the presence of a large number of job seekers and employers. Asia Pacific is expected to witness significant growth in the coming years, driven by the rising adoption of online recruitment and job search platforms in developing countries like India and China.

Overview WageScape's global job market data provide real-time, forward-looking insights into the international labor market. Covering diverse industries and regions, it supports workforce analytics, economic forecasting, and strategic planning, leveraging LinkedIn data, company data, and employee data.

Main Attributes • Job Titles: Across various sectors. • Locations: Country to city-specific details. • Job Descriptions: Roles and requirements. • Company Information: Names and sectors. • Posting Dates: Timeline of activity.

Coverage • Industries: Technology, healthcare, finance, manufacturing, retail, and more. • Geographical Reach: 62 countries, from national to local levels.

Scale and Quality Indicators • Data Volume: Over 5 million job postings data monthly. • Hiring Organizations: 15+ million worldwide. • High Precision: Rigorous validation.

Use Cases • Workforce Analytics: Analyze trends for HR decisions. • Economic Forecasting: Predict global trends. • Talent Acquisition: Improve recruitment strategies. • Market Research: Understand labor trends. • Strategic Planning: Inform business strategies.

Data Accessibility • Delivery Channels: Data-as-a-Service (DaaS). • Customizable Reports: Tailored to needs. • Integration: Seamless integration into existing systems.

Key Benefits • Real-Time Insights: Timely job market data for informed decisions. • Forward-Looking Data: Predict future global labor trends. • Comprehensive Coverage: Extensive industry and geographic data. • High Quality and Scale: Millions of job postings data monthly for robust analysis. • Actionable Insights: Enhance job modeling and workforce strategies globally.

Key Points WageScape's dataset is essential for navigating the global labor market. With extensive coverage, high-quality data, and actionable insights, it empowers businesses to make informed decisions, optimize workforce strategies, and stay competitive.

In 2025, there were estimated to be approximately 3.6 billion people employed worldwide, compared to 2.23 billion people in 1991 - an increase of around 1.4 billion people. There was a noticeable fall in global employment between 2019 and 2020, when the number of employed people fell from due to the sudden economic shock caused by the COVID-19 pandemic. Formal vs. Informal employment globally Worldwide, there is a large gap between the informally and formally employed. Most informally employed workers reside in the Global South, especially Africa and Southeast Asia. Moreover, men are slightly more likely to be informally employed than women. The majority of informal work, nearly 90 percent, is within the agricultural sector, with domestic work and construction following behind. Women’s employment As the number of employees has risen globally, so has the number of employed women. Overall, care roles such as nursing and midwifery have the highest shares of female employees globally. Moreover, while the gender pay gap has shrunk over time, it still exists. As of 2024, the uncontrolled gender pay gap was 0.83, meaning women made, on average, 83 cents per every dollar earned by men.

Abstract

The Egypt Labor Market Panel Surveys (ELMPSs) of 1998, 2006, and 2012 and Jordan Labor Market Panel Survey (JLMPS) of 2010 have become well-recognized data sources for labor market studies in the Middle East and North Africa (MENA). These two surveys have been used in numerous research endeavors including peer reviewed academic publications, dissertations, and international organization reports. As part of the same series of surveys, the Tunisia Labor Market Panel Survey (TLMPS) of 2014 is the first wave of what will eventually become a longitudinal survey of the Tunisian labor market. Being far richer than any currently available data, the TLMPS 2014 is a much-needed addition in a landscape of otherwise scarce publicly-accessible data on the Tunisian labor market. The TLMPS 2014 was collected in partnership between the Economic Research Forum (ERF) and the Tunisian National Institute of Statistics (INS).

Similarly to its Egyptian and Jordanian counterparts, the TLMPS 2014 is a nationally representative survey that features detailed information on households and individuals, especially in regards to labor market characteristics. As in other countries in the MENA region, Tunisia suffers from high unemployment, particularly for university graduates, youth, and women, and from low female labor force participation.

The survey allows for an in-depth investigation of current employment characteristics as well as analyses of broader labor market dynamics. For instance, analyses have already revealed the particularly long unemployment durations Tunisian youth experience, long even in comparison to other countries in the region.

For more information, see the paper(s) cited in the "Citations" section: (Assaad, Ragui, Samir Ghazouani, Caroline Krafft, and Dominique J. Rolando, 2016).

Geographic coverage

The sample covered urban/rural areas of each of Tunisia's governorates

Analysis unit

1- Households. 2- Individuals.

Universe

The survey covered a national sample of households and all households members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The initial sample frame included around 5,160 households drawn from a larger sample that is regularly used to conduct the quarterly survey on population and employment in Tunisia. This larger sample contained 18,000 households as of the last quarter of 2012. The drawing of the sample was done in two stages. In the first stage, 258 enumeration areas were randomly drawn according to the principle of probability proportional to size from the list of enumeration areas drawn up in the 2004 Census. This first sampling stage was carried out using 46 strata comprised of the urban/rural components of each of Tunisia's governorates. The final sample was made up of 253 clusters (out of a possible 40,377 nationally). In the second stage, 20 households were supposed to be drawn at random from each cluster. This procedure was, however, not strictly followed in the field.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey incorporates questionnaires to be administered at both the household and individual levels. At the household level, there was a general household questionnaire, as well as a questionnaire specifically about current migration, transfers, and agricultural and non-agricultural enterprises. At the individual level, there was a detailed questionnaire for working age individuals (15+) and an abbreviated version of the questionnaire for those 6-14 years old.

The main household questionnaire and the migration/enterprise questionnaire were designed to be answered by the most knowledgeable individual in the household, usually the head or the spouse of the head. Along with information on the characteristics of the dwelling, access to public services, and ownership of durables, the household questionnaire includes a full household roster with information on basic demographic characteristics, such as age, sex, and relationship to the head of household. The migration/enterprise questionnaire includes information on any family members currently abroad, remittances, and other transfers, such as child support and pensions. Data were gathered on both non-agricultural and agricultural enterprises, including assets used and net revenues.

The ELMPS and JLMPS had a single questionnaire for all individuals regardless of age. However, in Tunisia, a distinct questionnaire for individuals 6-14 was designed in order to more carefully incorporate measures of child labor. As very little child labor was detected even with this special design, in future LMPSs we plan to revert to a single questionnaire with a few additional questions targeted to children 6-14.

The questionnaire includes a variety of modules on labor market experience and outcomes and related issues. On the labor market side, it elicits information on the current labor market status of the individual, detailed job characteristics (for the employed), wage earnings and non-wage benefits (for wage workers) and participation in domestic and subsistence work. Those who work were asked about both primary and secondary jobs (if any). The questionnaire also includes a detailed labor market history starting from the first labor market status after leaving school and moving forward towards the present for those who ever worked. Further, there is a detailed section on return migration for those who ever worked abroad.

The labor market intersects with a number of other important life experiences, such as education, fertility, and marriage, which are also captured in the TLMPS individual questionnaire. For instance, there are modules on family background (parents and siblings), educational experiences, health, and residential mobility. For women, a section is devoted to fertility issues, the status of women in the household, and work-family issues such as child care and maternity leave. Data were also collected from both men and women on marriage and decisions around marriage, such as the incidence of kin marriage and living arrangements at marriage. Finally, there are modules on financial decision-making, with specific questions about savings and borrowing, as well as on the use of information technology.

Response rate

There were several different problems with non-response during the fielding. First, households often refused to respond entirely. Second, in completing the household survey, some individuals were not captured and some households refused or failed to answer the migration/enterprise questionnaire. In this section we discuss the patterns of non-response, which are incorporated into the weights, discussed below:

1. Non-response of the entire household While the initial goal was to collect data from 5,160 households, time pressures reduced the intended sample to 4,986 households. Of the 4,986 households initially selected, interviews were completed with only 4,521, generating an overall household non-response rate of 9.3%. Additionally, because several clusters were found not to have the requisite twenty households at the end of the data collection stage, additional households were added to some clusters to improve the response rate, leading to wide variation in the number of the households per cluster. The minimum number of households interviewed in a cluster was 8 and the maximum was 34. The mean was 19.7, and the median was 20, with the interquartile range going from 17 to 22 households.

After this additional work to add households to the sample, non-response rates at a cluster level ranged from 0% (complete response), which occurred for 29% of clusters, to a maximum of 62.5%. The mean non-response at the cluster level was 10.2%, the median was 6.7%, the 75th percentile was 13.3%, and the 90th percentile was 24.8%. This household non-response is incorporated in the weights at a cluster level, with the households that did respond within a cluster representing those that did not.

1. Non-response to child, adult, and migration/enterprise questionnaires As well as problems with non-response on the household level, there were problems with completing the child, adult, and migration/enterprise questionnaires. We developed weights to account for non-response to each of these questionnaires in their entirety. However, individuals often stopped answering partway through a questionnaire, suffered from incorrect skips, or other data problems, such that data is sometimes missing for a particular question within a questionnaire that contains some data. Additional data imputation techniques, implemented on a question-by-question basis, are required for these problems.

Employment Rate in the United States decreased to 59.90 percent in February from 60.10 percent in January of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This statistic shows the result of a survey on how optimistic respondents looking for a job were concerning the overall situation on the job market in Germany in 2014. In the period of consideration, about 60 percent of graduate medical students stated to see their chances on the job market as promising. Soon-to-be IT business engineers were the most optimistic in assessing their chances on the job market.

The size and share of the market is categorized based on Type (On Premises, Cloud-based) and Application (Enterprise, Job Seeker) and geographical regions (North America, Europe, Asia-Pacific, South America, and Middle-East and Africa).

In 2024, there were approximately 10.5 million men employed on a part-time basis in the United States. This was an increase from the previous year, when there were ten million part-time employed men.

Job Shop Management Software Market size was valued at USD 2.7 Billion in 2023 and is projected to reach USD 11 Billion by 2030, growing at a CAGR of 19% during the forecast period 2024-2030.

Global Job Shop Management Software Market Drivers

The growth and development of the Job Shop Management Software Market is attributed to certain main market drivers. These factors have a big impact on how Job Shop Management Software are demanded and adopted in different sectors. Several of the major market forces are as follows:

Increasing Need for Streamlined Operations: Job shop management software helps job shops run more efficiently by providing capabilities like order tracking, inventory management, and scheduling. Such software is becoming more and more popular due to the growing demand for productivity and efficiency.

Automation’s growth and Industry 4.0 trends: There’s a big push in manufacturing processes toward automation and digitization with the introduction of Industry 4.0. The integration of several production factors through the use of job shop management software results in increased productivity and decreased downtime.

Put an emphasis on Cost Reduction and Resource Optimization: Using job shop management software can save costs by improving resource allocation, cutting down on material waste, and improving scheduling. Businesses are increasingly searching for ways to reduce expenses without sacrificing quality in a competitive market.

Growing Complexity in Manufacturing Processes: Work shops frequently deal with a range of projects with different specifications. To guarantee seamless operations, this complexity necessitates sophisticated management solutions. Software for managing job shops provides the features needed to successfully manage such complexity.

Growing Adoption of Cloud-Based Solutions: Small to medium-sized job shops find cloud-based job shop management software appealing due to its accessibility, scalability, and flexibility. The market for job shop management software is developing as a result of the increasing use of cloud computing across industries.

Focus on Real-Time Data Analysis: Work shop management software offers in-the-moment insights into a range of production-related topics, such as order status, machine utilization, and inventory levels. Businesses are making more and more decisions based on data, thus there is a growing need for software with advanced analytics features.

Compliance Requirements and Quality Standards: In order to satisfy client expectations, job shops must adhere to industry rules and uphold high standards of quality. Manufacturers are drawn to job shop management software because it frequently has tools for compliance management, quality control, and traceability.