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 ** percent of the companies reporting the technology will create jobs and * percent expecting the technology to displace jobs. Meanwhile, artificial intelligence (AI) is expected to result in more significant labor market disruptions, with ** percent of organizations expecting the technology to displace jobs and ** percent expecting AI to create jobs.

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.

Data and analysis of Washington's employment conditions, economy, job market and workforce. These reports can help make informed career, hiring and policy decisions.

The global market size of Labor is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Labor Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Labor industry. The key insights of the report:
1.The report provides key statistics on the market status of the Labor manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Labor industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Labor Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Labor as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Labor market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

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Workforce Analytics Market Size 2025-2029

The workforce analytics market size is forecast to increase by USD 3.27 billion, at a CAGR of 19.1% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing demand for efficient workforce management and recruitment. Companies are recognizing the value of leveraging data-driven insights to optimize their workforce, leading to increased adoption of workforce analytics solutions. Another key trend in the market is the growing use of mobile applications for workforce analytics, enabling real-time access to data and analytics from anywhere. However, the market also faces challenges, including the lack of a skilled workforce capable of effectively implementing and utilizing these advanced analytics tools. As the market continues to evolve, companies seeking to capitalize on opportunities and navigate challenges effectively must prioritize investments in workforce analytics solutions and focus on building a skilled workforce to maximize the value of their data.

What will be the Size of the Workforce Analytics Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, driven by the ever-increasing importance of data-driven decision making in various sectors. Cost optimization, data visualization, and data warehousing are integral components of workforce analytics, enabling organizations to gain valuable insights from their workforce data. Process automation and employee development are also key areas of focus, as they help streamline operations and enhance employee skills. Performance management and organizational network analysis provide valuable insights into employee productivity and team dynamics. ETL processes and risk management ensure data accuracy and security, while recruitment optimization and career pathing facilitate effective talent acquisition and retention. Predictive modeling and sentiment analysis aid in anticipating workforce trends and employee sentiment, respectively. Data security and strategic workforce planning are essential for mitigating risks and ensuring long-term success. Machine learning and natural language processing are advanced technologies that are increasingly being adopted for data analysis and processing. Workforce analytics encompasses a range of applications, from compensation analysis and employee satisfaction to diversity and inclusion and leadership development. These areas are interconnected and evolve continuously, with new technologies and trends shaping the market landscape. The ongoing integration of these applications into comprehensive workforce analytics solutions enables organizations to optimize their workforce and gain a competitive edge.

How is this Workforce Analytics Industry segmented?

The workforce analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userRetailBFSITelecom and ITHealthcareOthersApplicationLarge enterprisesSmall and medium sized enterpriseDeploymentCloudOn-premiseServiceConsulting ServicesSystem IntegrationManaged ServicesGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW)

By End-user Insights

The retail segment is estimated to witness significant growth during the forecast period.In today's dynamic business environment, retail organizations face increasing pressure to optimize their workforce to stay competitive. The retail industry's growth is driven by factors such as changing market economics, rising competition from e-commerce, and evolving customer demands. To meet these challenges, retailers are investing in their workforce, recognizing its crucial role in driving business success. Workforce optimization strategies encompass various approaches, including 360-degree feedback, organizational network analysis, and social network analysis, to enhance employee performance and engagement. Headcount planning, aided by cloud computing, enables retailers to manage their workforce effectively and adapt to seasonal fluctuations. Regression analysis, statistical analysis, and time series analysis help retailers identify trends and make data-driven decisions. Strategic workforce planning, succession planning, and talent acquisition are essential components of a robust workforce strategy. Employee development, cost optimization, data cleaning, and natural language processing are critical for maintaining a skilled and productive workforce. Data mining, ETL processes, data warehousing, and business intelligence provide valuable insights into workforce performance and trends. Retention strategies,

The Department of Economic Research Data Index provides information about the economy and labor market in Massachusetts. It includes links to data tools, analytic reports, data visualizations, dashboards and other resources in the following areas:

• Unemployment and Labor Force Data
• Employment Information by Industry
• Employment Information by Occupation
• Information on Massachusetts Employers
• Location Data

This dataset includes data for an analysis of labor demand characteristics and workforce training needs in the metropolitan areas of La Paz-El Alto, Cochabamba, and Santa Cruz—large cities in Bolivia (Related publication only available in Spanish). This information is contrasted with a sample from intermediate and small cities in the country. Labor demand data for large cities comes from a survey of companies conducted in 2015 and 2016, while data for intermediate and small cities is derived from a survey conducted between 2016 and 2017. The document presents key findings on the productive characteristics of cities, company profiles, and workforce dynamics, including recruitment and selection processes, employee turnover, reasons for dismissals, training, demand for and valuation of skills, among other factors. Finally, it outlines policy implications for Bolivia’s labor market.

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.

The Labor Market Intelligence Platform market is rapidly evolving, driven by the increasing demand for accurate workforce analytics and insights that can guide strategic decision-making for organizations. These platforms aggregate, analyze, and present data related to employment trends, skill requirements, and labor

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.

📂 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

Deduplicated aggregated job data by area and occupation with salary data. Data is available for USA and territories by FIPS area codes, ONET occupation code, NAIC industry code, education group, and experience group, with USD salary information by month, quarter, and year time frames. Data includes aggregations for both active jobs in given time frame and those first posted in given time frame.

1B+ job posts 42k+ job sources 5M+ unique employers 4.8M new jobs per month 18 years of data

At iQuery, we provide unparalleled insight into the labor market through our proprietary aggregated jobs data. By combining historical data with real-time job postings, our platform captures employment trends as they unfold—offering powerful predictive capabilities for workforce analysis, planning, and development.

Our specialized team of developers processes and refines 7 to 10 million job listings daily, collected from a wide array of online sources including public and private job boards, government portals, healthcare systems, and various other employment websites. We ensure data freshness by validating and de-duplicating postings and conducting daily checks to confirm their active status—making our datasets among the most accurate and current in the industry.

Our dedicated Data Services Team enhances the dataset by assigning standardized taxonomy codes for occupation (ONET), employer industry (NAICS), location (FIPS), education level, and experience requirements. We also offer crosswalk capabilities between Classification of Instructional Programs (CIP) codes and federal taxonomies, enabling education providers to align curricula with real-time and projected workforce needs. Our proprietary taxonomy extends to skills, tools, and certifications, further enriching each job posting for granular labor market analysis.

With a comprehensive blend of real-time and historical data, our platform supports economic development by tracking workforce dynamics across occupations, industries, and skill sets. Our in-house economist and analysts generate reliable labor market forecasts—including unemployment trends—often outperforming traditional forecasting models.

Our data empowers a wide range of stakeholders:

Governments can assess local labor supply to attract employers and inform policy. Researchers can uncover trends and model future workforce shifts. Employers can locate optimal labor pools for hiring needs. Colleges and universities can tailor programs and credentials to match employer demand in specific regions. iQuery delivers a data-rich foundation for workforce planning, policy development, and educational alignment—driving smarter decisions in a dynamic labor market.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

Temporary Labor Market size is projected to reach over USD 794.35 bn by 2032 from a value of USD 556.04 bn in 2024 and is projected to grow by USD 571.49 bn in 2025, registering a CAGR of 4.6% from 2025 to 2032.

The New York State Department of Labor has labor market analysts in 10 regions across the state. This data set outlines where the labor market analysts are located by labor market region.

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/

The global Labor Market Intelligence Platform market is projected to grow from USD 3,455.3 million in 2025 to USD 10,842.8 million by 2033, exhibiting a CAGR of 16.5% from 2025 to 2033. The market growth is primarily driven by the increasing demand for data-driven insights into labor market trends, skills gaps, and talent availability. The rising adoption of cloud-based platforms, the growing need for talent management and workforce planning, and government initiatives to enhance labor market efficiency are further contributing to market expansion. North America is expected to dominate the Labor Market Intelligence Platform market throughout the forecast period, owing to the presence of well-established vendors, early adoption of technology, and a large pool of skilled professionals. Asia Pacific is anticipated to witness significant growth in the coming years, driven by the increasing demand for talent in emerging economies and government initiatives to improve labor market information systems. The key players in the market include LinkedIn, Lightcast, Claro Analytics, Coresignal, Horsefly, Chmura, Talismatic, Textkernel, WageScape, Liepin, BOSS Zhipin, 51Job, and Zhilian Zhaopin. These companies offer a range of solutions to meet the diverse needs of organizations, including data-driven insights, talent management tools, and recruitment solutions.

Note: Updates to this data product are discontinued. County boundaries do not always accurately define local economies. Commuting zones and Labor Market Areas combine counties into units intended to more closely reflect the geographic interrelationships between employers and labor supply.

The global Labor Market Intelligence Platform market is experiencing robust growth, driven by increasing demand for data-driven decision-making within HR and talent acquisition departments. The market, estimated at $5 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of advanced analytics and AI-powered tools is enhancing the ability of organizations to predict future labor market trends, optimize recruitment strategies, and improve workforce planning. Secondly, the increasing complexity of the global talent landscape, coupled with skill shortages in various sectors, necessitates sophisticated platforms for comprehensive labor market analysis. Finally, the growing need for compliance with labor regulations and effective diversity, equity, and inclusion (DE&I) initiatives further drives the adoption of these platforms. Leading players like LinkedIn, Lightcast, and others are actively innovating to meet these evolving demands, expanding their platform functionalities to incorporate advanced features such as predictive modeling and real-time data visualization. The market's segmentation reveals a diverse landscape of platform types, catering to specific needs across various industries and company sizes. While detailed segment-specific data isn't provided, a logical assumption considering the market's drivers would suggest robust growth in segments focused on AI-powered predictive analytics, integration with applicant tracking systems (ATS), and specialized solutions tailored to specific industries (e.g., healthcare, technology). Geographical segmentation is expected to show strong growth across North America and Europe, driven by early adoption and advanced technological infrastructure. However, emerging markets in Asia-Pacific are poised for significant expansion in the coming years, driven by increasing digitalization and economic growth. While challenges exist such as data privacy concerns and the need for robust data integration capabilities, the overall market outlook remains optimistic, promising continued growth and innovation in the years to come.

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