The O*NET Database contains hundreds of standardized and occupation-specific descriptors on almost 1,000 occupations covering the entire U.S. economy. The database, which is available to the public at no cost, is continually updated by a multi-method data collection program. Sources of data include: job incumbents, occupational experts, occupational analysts, employer job postings, and customer/professional association input.

Data content areas include:

• Worker Characteristics (e.g., Abilities, Interests, Work Styles)
• Worker Requirements (e.g., Education, Knowledge, Skills)
• Experience Requirements (e.g., On-the-Job Training, Work Experience)
• Occupational Requirements (e.g., Detailed Work Activities, Work Context)
• Occupation-Specific Information (e.g., Job Titles, Tasks, Technology Skills)

Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

Comprehensive employment database containing detailed job market data covering all Israeli cities and industries, including real-time position availability, salary ranges, skill requirements, and employment trends across technology, finance, healthcare, and other key sectors

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 for Poland: A Comprehensive Resource for Employment Insights

Techsalerator's Job Openings Data for Poland is an essential tool for businesses, job seekers, and labor market analysts. This dataset offers a detailed overview of job openings across various sectors in Poland, consolidating and categorizing job-related information from multiple sources, including company websites, job boards, and recruitment agencies.

Key Data Fields

• Job Posting Date: Captures the date a job is listed. This helps job seekers and HR professionals stay updated on the latest opportunities and trends.
• Job Title: Specifies the position being advertised. This aids in categorizing and filtering job openings based on industry roles and career interests.
• Company Name: Lists the hiring company. This information assists job seekers in targeting their applications and helps businesses track competitors and market trends.
• Job Location: Provides the job's geographic location within Poland. Job seekers use this to find regional opportunities, while employers analyze regional talent and market conditions.
• Job Description: Includes details about responsibilities, required qualifications, and other relevant aspects. This is vital for candidates to determine if they meet the requirements and for recruiters to communicate expectations clearly.

Top 5 Job Categories in Poland

1. Information Technology (IT): High demand for software developers, IT support specialists, and cybersecurity experts as the digital sector continues to expand.
2. Healthcare: Opportunities for doctors, nurses, medical technicians, and public health workers, driven by both public and private sector needs.
3. Finance and Accounting: Roles in financial analysis, accounting, and investment, reflecting Poland's growing financial services sector.
4. Engineering and Manufacturing: High demand for engineers and technicians across various fields, including mechanical, civil, and electrical engineering, due to ongoing industrial growth.
5. Education: Positions for teachers, administrators, and educational consultants, reflecting the country’s commitment to improving educational standards.

Top 5 Employers in Poland

• Polska Grupa Energetyczna (PGE): A leading energy provider with frequent openings in engineering, operations, and project management.
• PKN Orlen: The largest oil refiner in Poland, offering roles in operations, engineering, and management.
• Allegro: A major e-commerce platform with opportunities in IT, marketing, and logistics.
• Capgemini: A global consulting firm with positions in IT consulting, project management, and business analysis.
• University of Warsaw: One of the largest and most prestigious universities in Poland, regularly hiring for academic, administrative, and research roles.

Accessing Techsalerator’s Data

To access Techsalerator’s Job Openings Data for Poland, please contact info@techsalerator.com with your specific needs. We will provide a customized quote based on the data fields and records you require, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields: - Job Posting Date - Job Title - Company Name - Job Location - Job Description - Application Deadline - Job Type (Full-time, Part-time, Contract) - Salary Range - Required Qualifications - Contact Information

Techsalerator’s dataset is a valuable tool for staying informed about job openings and employment trends in Poland, assisting businesses, job seekers, and analysts in making informed decisions.

Global IT Jobs Analysis

A Detailed Investigation of Salary, Location, and Job Requirements

By [source]

About this dataset

This dataset contains valuable insights into current job opportunities in the information technology (IT) sector all around the world. It offers an overview of available jobs and relevant data such as company, location, salary and links to further information. With this insight, one has the chance to better understand what it takes to land a remote or data-science job in today's global market. The ever increasing demand for IT workforce puts technical skills at a premium, so understanding exactly what employers are searching for can give potential employees an edge in catching the eye of these businesses! Digging through this dataset can provide details on current trends in terms of salary expectations and geographical locations where these roles are most popular. Beyond that, get an idea about which abilities seem most valuable when it comes to remote or data-science positions. Use this arsenal of knowledge to take your career goals into your own hands now!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides an opportunity to explore the remote and data-science job opportunities around the world. Using this dataset, you can analyze trends in job requirements, salary packages offered, location of available jobs and more. With the knowledge gained from this data set, individuals and companies can make more informed decisions about pursuing a certain path in their career or hiring for their business.

The dataset includes columns with important information such as Job title, Company offering the job, Location of the position , Salary offered for that position and a Link to its respective posting. Using these columns you can analyze various factors regarding global IT Jobs availability over different locations in alignment with salary offered for positions and any specific skill sets sought out by companies .

To get executable insights from this data set users should first load it into their respective computing environment (Python or R). After loading it in your environment users should start off by exploring Groupby statements along factors like Companies offering jobs ,Salary offered ,Location etc. followed by descriptive statistics like mean & median of Salary Levels per country/region etc. After getting basic insight about summary statistics for various factors belonging all together within “Job” range user could move forward to look over individual cases (specific skill sets) after which they could filter out & generate valueable insights needed .

With our comprehensive understanding of global supply & demand rates individuals/corporations could always use these datasets to help them keep track on talent acquisition landscape when they hire globally or relocating teams as companies who need such information would greatly benefit from versatile tools like this one that offer valuable actionsable insights on an ongoing basis depending upon dayers choosing!

Research Ideas

• Identifying the most in-demand skills and employment requirements for remote data science and IT jobs, across different countries and regions.
• Developing a prediction model to forecast future salary expectations for data science professionals based on location, company, job type, etc.
• Building an interactive dashboard with visualizations showing differences in job requirements (by level of experience or education), salary comparison across geographies as well as potential career paths one can pursue within the IT or Data Science fields

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: Job_listing.csv | Column name | Description | |:--------------|:---------------------------------------------------| | Job | The title of the job listing. (String) | | Company | The name of the company offering the job. (String) | | Location | The geographic location of the job. (String) | | Salary | The salary offere...

United States Employment: sa: Part Time: ER: Slack Work Or Business Conditions data was reported at 3,042.000 Person th in Jun 2018. This records an increase from the previous number of 3,004.000 Person th for May 2018. United States Employment: sa: Part Time: ER: Slack Work Or Business Conditions data is updated monthly, averaging 2,323.000 Person th from May 1955 (Median) to Jun 2018, with 758 observations. The data reached an all-time high of 6,972.000 Person th in Mar 2009 and a record low of 773.000 Person th in Apr 1966. United States Employment: sa: Part Time: ER: Slack Work Or Business Conditions data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G014: Current Population Survey: Employment: Seasonally Adjusted.

History of Work

Here you find the History of Work resources as Linked Open Data. It enables you to look ups for HISCO and HISCAM scores for an incredible amount of occupational titles in numerous languages.

Data can be queried (obtained) via the SPARQL endpoint or via the example queries. If the Linked Open Data format is new to you, you might enjoy these data stories on History of Work as Linked Open Data and this user question on Is there a list of female occupations?.

NEW version - CHANGE notes

This version is dated Apr 2025 and is not backwards compatible with the previous version (Feb 2021). The major changes are: - incredible simplification of graph representation (from 81 to 12); - use of sdo (https://schema.org/) rather than schema (http://schema.org); - replacement of prov:wasDerivedFrom with sdo:isPartOf to link occupational titles to originating datasets; - etl files (used for conversion to Linked Data) now publicly available via https://github.com/rlzijdeman/rdf-hisco; - update of issues with language tags; - specfication of language tags for english (eg. @en-gb, instead of @en); - new preferred API: https://api.druid.datalegend.net/datasets/HistoryOfWork/historyOfWork-all-latest/sparql (old API will be deprecated at some point: https://api.druid.datalegend.net/datasets/HistoryOfWork/historyOfWork-all-latest/services/historyOfWork-all-latest/sparql ) .

There are bound to be some issues. Please leave report them here.

Figure 1. Part of model illustrating the basic relation between occupations, schema.org and HISCO. https://druid.datalegend.net/HistoryOfWork/historyOfWork-all-latest/assets/601beed0f7d371035bca5521" alt="hisco-basic">

Figure 2. Part of model illustrating the relation between occupation, provenance and HISCO auxiliary variables. https://druid.datalegend.net/HistoryOfWork/historyOfWork-all-latest/assets/601beed0f7d371035bca551e" alt="hisco-aux">

Salary and employment data for academic/research physicians

United States US: Employment In Industry: Modeled ILO Estimate: Female: % of Female Employment data was reported at 8.347 % in 2017. This records an increase from the previous number of 8.251 % for 2016. United States US: Employment In Industry: Modeled ILO Estimate: Female: % of Female Employment data is updated yearly, averaging 9.952 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 13.606 % in 1991 and a record low of 7.916 % in 2010. United States US: Employment In Industry: Modeled ILO Estimate: Female: % of Female Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Employment and Unemployment. Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for information systems database systems in the U.S.

Techsalerator's Job Openings Data for Turkey: A Comprehensive Resource for Employment Insights

Techsalerator's Job Openings Data for Turkey provides an in-depth and thorough overview of job opportunities across various sectors within the country. This dataset consolidates information from diverse sources, including company websites, job boards, and recruitment agencies, offering invaluable insights for businesses, job seekers, and labor market analysts.

Key Data Fields

• Job Posting Date: Records the date when a job listing is published. This is crucial for staying updated on the latest job opportunities and trends.
• Job Title: Identifies the position being advertised. Helps in categorizing and filtering job openings based on industry roles and career interests.
• Company Name: Lists the organization offering the job. Assists job seekers in targeting their applications and helps businesses track competitors and market trends.
• Job Location: Specifies the geographic location within Turkey. Useful for job seekers to find regional opportunities and for employers to analyze regional talent pools and market conditions.
• Job Description: Contains details about job responsibilities, required qualifications, and other relevant aspects. Vital for candidates to assess their fit and for recruiters to communicate job expectations clearly.

Top 5 Job Categories in Turkey

• Information Technology (IT): High demand for software developers, IT support specialists, and cybersecurity experts, driven by ongoing technological advancements.
• Healthcare: Opportunities for doctors, nurses, medical technicians, and public health workers, reflecting the sector's growth and development.
• Education: Positions for teachers, administrators, and educational consultants, supporting the country's focus on improving education standards.
• Engineering and Construction: Demand for civil, mechanical, and electrical engineers, along with skilled laborers, due to ongoing infrastructure projects and urban development.
• Finance and Banking: Roles in financial analysis, banking operations, and investment management, driven by the financial sector's expansion.

Top 5 Employers in Turkey

• Koç Holding: A leading conglomerate with frequent openings in finance, management, IT, and operations across its various subsidiaries.
• Turkish Airlines: The national carrier offers roles in aviation management, engineering, customer service, and logistics.
• Beko (Arcelik): A major home appliances manufacturer with positions in engineering, product development, sales, and customer service.
• Sabancı Holding: A prominent industrial and financial conglomerate hiring for roles in finance, marketing, and business management.
• Halkbank: A leading financial institution with opportunities in banking operations, financial analysis, and customer service.

Accessing Techsalerator’s Data

To access Techsalerator’s Job Openings Data for Turkey, please contact info@techsalerator.com with your specific requirements. We will provide a customized quote based on the data fields and records you need, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

• Job Posting Date
• Job Title
• Company Name
• Job Location
• Job Description
• Application Deadline
• Job Type (Full-time, Part-time, Contract)
• Salary Range
• Required Qualifications
• Contact Information

Techsalerator’s dataset is a valuable resource for those looking to stay informed about job openings and employment trends in Turkey, assisting businesses, job seekers, and analysts in making strategic decisions.

United States CCI: Present Situation: sa: Employment: Jobs Plentiful data was reported at 31.700 % in Apr 2025. This records a decrease from the previous number of 33.600 % for Mar 2025. United States CCI: Present Situation: sa: Employment: Jobs Plentiful data is updated monthly, averaging 20.600 % from Feb 1967 (Median) to Apr 2025, with 637 observations. The data reached an all-time high of 56.700 % in Mar 2022 and a record low of 2.800 % in Nov 1982. United States CCI: Present Situation: sa: Employment: Jobs Plentiful data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.H049: Consumer Confidence Index. [COVID-19-IMPACT]

Captures information on disability beneficiaries that are participating in one of the "the return to work initiative"; to help become self sufficient, and to limit reliance on disability benefits.

Research dissemination and knowledge translation are imperative in social work. Methodological developments in data visualization techniques have improved the ability to convey meaning and reduce erroneous conclusions. The purpose of this project is to examine: (1) How are empirical results presented visually in social work research?; (2) To what extent do top social work journals vary in the publication of data visualization techniques?; (3) What is the predominant type of analysis presented in tables and graphs?; (4) How can current data visualization methods be improved to increase understanding of social work research? Method: A database was built from a systematic literature review of the four most recent issues of Social Work Research and 6 other highly ranked journals in social work based on the 2009 5-year impact factor (Thomson Reuters ISI Web of Knowledge). Overall, 294 articles were reviewed. Articles without any form of data visualization were not included in the final database. The number of articles reviewed by journal includes : Child Abuse & Neglect (38), Child Maltreatment (30), American Journal of Community Psychology (31), Family Relations (36), Social Work (29), Children and Youth Services Review (112), and Social Work Research (18). Articles with any type of data visualization (table, graph, other) were included in the database and coded sequentially by two reviewers based on the type of visualization method and type of analyses presented (descriptive, bivariate, measurement, estimate, predicted value, other). Additional revi ew was required from the entire research team for 68 articles. Codes were discussed until 100% agreement was reached. The final database includes 824 data visualization entries.

Georgia Employment: Business Sector: by Economic Activity: NACE 1.1: Health and Social Work data was reported at 68,609.000 Person in Jun 2018. This records an increase from the previous number of 67,477.030 Person for Mar 2018. Georgia Employment: Business Sector: by Economic Activity: NACE 1.1: Health and Social Work data is updated quarterly, averaging 56,442.500 Person from Mar 2006 (Median) to Jun 2018, with 50 observations. The data reached an all-time high of 68,609.000 Person in Jun 2018 and a record low of 48,258.000 Person in Dec 2011. Georgia Employment: Business Sector: by Economic Activity: NACE 1.1: Health and Social Work data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.G005: Employment.

The Quarterly Census of Employment and Wages (QCEW) program (also known as ES-202) collects employment and wage data from employers covered by New York State's Unemployment Insurance (UI) Law. This program is a cooperative program with the U.S. Bureau of Labor Statistics. QCEW data encompass approximately 97 percent of New York's nonfarm employment, providing a virtual census of employees and their wages as well as the most complete universe of employment and wage data, by industry, at the State, regional and county levels. "Covered" employment refers broadly to both private-sector employees as well as state, county, and municipal government employees insured under the New York State Unemployment Insurance (UI) Act. Federal employees are insured under separate laws, but are considered covered for the purposes of the program. Employee categories not covered by UI include some agricultural workers, railroad workers, private household workers, student workers, the self-employed, and unpaid family workers. QCEW data are similar to monthly Current Employment Statistics (CES) data in that they reflect jobs by place of work; therefore, if a person holds two jobs, he or she is counted twice. However, since the QCEW program, by definition, only measures employment covered by unemployment insurance laws, its totals will not be the same as CES employment totals due to the employee categories excluded by UI. Industry level data from 1975 to 2000 is reflective of the Standard Industrial Classification (SIC) codes.

The "Quality of employment" framework developed under the lead of UNECE (United Nations Economic Commission for Europe) represents a neutral and comprehensive approach to assess quality of employment in its multiple facets. It defines 68 indicators on seven dimensions that address employment quality from the perspective of the employed person. Its design also facilitates international comparison. For statistical institutes, researchers and policy users looking to build and analyse datasets using these indicators, the framework is explained in a Handbook on measuring quality of employment published by UNECE. Using the UNECE framework, Eurostat has compiled data on employment quality for the EU countries that is provided in the Eurostat database.

LFS in one of the sources which provides data for filling some of the indicators. The section 'Quality of employment' reports annual results from the EU-LFS concerning some of those indicators.

In particular:

• Long working hours in main job: percentage of employed persons usually working 49 hours or more per week;
• Weekly working hours: Average number of usual weekly working hours of employed persons;
• Work on weekends: Percentage of employed persons usually working at Saturday or Sunday;
• Job tenure Percentage of employed persons by duration of employment with current employer by number of years;
• Temporary employment agency workers: Percentage of employed persons working for a temporary work agency;
• Precarious employment: Percentage of employees with a short-term contract of up to 3 months.

More information on Eurostat indicators about Quality of employment is available on the Quality of employment webpage.

General information on the EU-LFS can be found in the ESMS page for 'https://ec.europa.eu/eurostat/cache/metadata/en/employ_esms.htm" target="_parent">Employment and unemployment (LFS). Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

This dataset contains the up-to-date metadata on Work Zone feeds that meet the Work Zone Data Exchange (WZDx) specifications and is registered with USDOT ITS DataHub. The current work zone data from each feed can be accessed through their respective API links. Some links provide direct access, while others require a user to create their own API access key first. Please see the attached API Key Instructions document to learn how to sign up for API keys for the requisite feeds. The ITS JPO has collections from 23 states covering various parts of the time period from 10/2019 to 08/2024 depending on when the feed was active. The data is split into two archive files, the raw data contains the collection of .json or .geojson files exactly as they were on the individual state’s WZDx feed at the time of collection. The processed data is organized by work zone, so that as information about the work zone changed through feed updates they would be collected in a single file for that work zone. To request access fill out the form here.

LinkedIn is a widely used professional networking platform that hosts millions of job postings. This dataset contains 1.3 million job listings scraped from LinkedIn in the year 2024.

This dataset can be used for various research tasks such as job market analysis, skills mapping, job recommendation systems, and more.

If you find this dataset valuable, please upvote 😊💼

This is the same master dataset that powers SkillExplorer

Interesting Task Ideas:

1. Practice data cleaning on raw data.
2. Analyze the most in-demand job titles or industries in different cities or countries.
3. Identify the top companies hiring for specific job positions.
4. Utilize the skills data to determine the most sought-after skills in different job categories.
5. Build a job recommendation system based on user profiles and job listing data.
6. Discover patterns in job types or levels across different industries.
7. Identify skill gaps in the job market to inform educational or training programs.
8. Explore the relationship between job title and required skills.

Photo by Clem Onojeghuo on Unsplash