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

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

Key Features:

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

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

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

Context

This dataset was created by our in-house Web Scraping and Data Mining teams at PromptCloud and DataStock. You can download the full dataset here. This sample contains 30K records. You can download the full dataset here

Content

Total Records Count: 1042684  Domain Name: careerbuilder.usa.com  Date Range: 01st Oct 2020 - 31st Dec 2020   File Extension: ldjson

Available Fields : uniq_id, crawl_timestamp, url, job_title, company_name, city, state, post_date, job_description, job_type, apply_url, job_board, geo, job_post_lang, inferred_iso2_lang_code, inferred_iso3_lang_code, test1_cities, test1_states, site_name, html_job_description, domain, postdate_yyyymmdd, predicted_language, test1_inferred_city, test1_inferred_state, test1_inferred_country, inferred_city, inferred_state, inferred_country, inferred_salary_currency, has_expired, last_expiry_check_date, latest_expiry_check_date, duplicate_status, dataset, is_remote, postdate_in_indexname_format, fitness_score 

Acknowledgements

We wouldn't be here without the help of our in house web scraping and data mining teams at PromptCloud, DataStock and live job data from JobsPikr.

Inspiration

This dataset was created keeping in mind our data scientists and researchers across the world.

The number of employed persons in The United States increased to 163366 Thousand in June of 2025 from 163273 Thousand in May of 2025. This dataset provides - United States Employed Persons - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

Context

This dataset was created by our in-house Web Scraping and Data Mining teams at PromptCloud and DataStock. You can download the full dataset here. This sample contains 30K records. You can download the full dataset here

Content

Total Records Count : 4451780  Domain Name : Indeed.usa.com  Date Range : 01st Jan 2022 - 31st Mar 2022   File Extension : ldjson

Available Fields : url, job_title, category, company_name, city, state, country, post_date, occupation_category, job_description, job_type, valid_through, html_job_description, extra_fields, uniq_id, crawl_timestamp, job_board, geo, job_post_lang, inferred_iso2_lang_code, is_remote, test1_cities, test1_states, test1_countries, site_name, domain, postdate_yyyymmdd, predicted_language, inferred_iso3_lang_code, test1_inferred_city, test1_inferred_state, test1_inferred_country, inferred_city, inferred_state, inferred_country, has_expired, last_expiry_check_date, latest_expiry_check_date, dataset, postdate_in_indexname_format, segment_name, duplicate_status, job_desc_char_count, ijp_reprocessed_flag_1, ijp_reprocessed_flag_2, ijp_reprocessed_flag_3, ijp_is_production_ready, fitness_score  

Acknowledgements

We wouldn't be here without the help of our in house web scraping and data mining teams at PromptCloud, DataStock and live job data from JobsPikr.

Inspiration

This dataset was created keeping in mind our data scientists and researchers across the world.

This dataset is about books. It has 1 row and is filtered where the book is The end of loyalty : the rise and fall of good jobs in America. It features 7 columns including author, publication date, language, and book publisher.

This dataset provides a focused collection of 1,000 job postings for Machine Learning-related roles located across the United States. The data was gathered between late 2024 and early 2025, directly sourced from various company career pages and major job boards. It includes detailed job descriptions and associated company information, offering valuable insights into the current landscape of the machine learning job market.

Columns

• job_posted_date: The date when the job advertisement was originally published (format: YYYY-MM-DD).
• company_address_locality: The city or local area where the job is situated or where the company is based.
• company_address_region: The specific U.S. state or larger region identifying the job's location.
• company_name: The trading name of the organisation that posted the job vacancy.
• company_website: The official web address for the company.
• company_description: A concise overview or mission statement of the company.
• job_description_text: The full and unedited text of the job description as it appeared in the initial posting.
• seniority_level: The required professional experience level for the role, such as Internship, Entry level, or Mid-Senior.
• job_title: The complete title given to the job vacancy.

Distribution

The dataset is typically provided in a CSV file format. It contains 1,000 individual job postings. Specific numbers for rows or records beyond this total are not available.

Usage

This dataset is ideal for: * Job Market Analysis: Gaining insights into trends in machine learning and AI job opportunities. * Career Planning: Helping job seekers understand required skills, roles, and companies in the ML field. * Recruitment Strategy: Assisting recruiters and HR professionals in benchmarking job requirements and compensation. * Academic Research: Supporting studies on labour market dynamics, skill demand, and geographical distribution of tech jobs. * Salary Benchmarking: Although not direct salary data, job descriptions often contain clues for salary expectations.

Coverage

The dataset's geographic scope covers various locations within the United States. The time range for data collection is between late 2024 and early 2025. No specific notes on data availability for particular demographic groups or years are provided.

License

CC-BY

Who Can Use It

• Data Scientists: For market analysis and trend identification.
• Machine Learning Engineers: For career insights and skill development.
• Job Seekers: To discover relevant opportunities and prepare for applications.
• Recruiters and Human Resources Professionals: For talent acquisition and market intelligence.
• Market Researchers: To analyse industry demand and regional variations.
• Students and Academics: For research projects and understanding the professional landscape.

Dataset Name Suggestions

• US Machine Learning Job Postings
• AI/ML Job Market USA
• United States ML Career Data
• Machine Learning Roles in the US

Attributes

Original Data Source: Machine Learning Job Postings in the US

This dataset contains information about job offers for data scientists in companies based in the United States of America (USA). It was obtained from the Google Jobs API via serpAPI. The dataset aims to provide insights into the job market for data scientists in the USA, assisting individuals in understanding opportunities and aiding companies in recruitment efforts. It is also valuable for researchers looking to explore trends and patterns within this specific job market.

Columns

• ID: A unique identifier for each job offer.
• title: The job title of the position advertised.
• company: The name of the company posting the job.
• announcement: The platform or location where the job was posted.
• description: The detailed job description.

Distribution

The dataset is typically provided in a CSV file format. It includes approximately 790 records, detailing various aspects of data scientist job offers. The structure is tabular, with distinct columns for job attributes.

Usage

This dataset is ideally suited for: * Individuals seeking to understand the current job market for data scientists in the USA, helping with career planning and job searching. * Companies looking to recruit data scientists, enabling them to analyse market demand and competitive offerings. * Researchers interested in exploring employment trends, salary patterns, or specific skill requirements within the data science field in the USA.

Coverage

The dataset focuses exclusively on job offers for data scientists in the United States of America. The data pertains to 2023 job descriptions. Users should be aware that the originating API source may not include all job offers across the USA, and the information provided by companies may not always be entirely up-to-date or accurate.

License

CC0

Who Can Use It

• Job seekers: To identify potential roles and understand market expectations.
• Recruitment agencies and HR professionals: For talent acquisition strategy and competitive analysis.
• Academic researchers and data analysts: To conduct studies on labour market dynamics and skill gaps.
• Educational institutions: To inform curriculum development based on industry demand.

Dataset Name Suggestions

• USA Data Scientist Job Market 2023
• US Data Science Vacancies
• American Data Scientist Roles 2023
• Data Scientist Jobs USA 2023

Attributes

Original Data Source: 2023 Data Scientists Jobs Descriptions

The Better Jobs Index is a tool for comparative analysis of labor markets in Latin America. This index evaluates the state of employment in the region through two dimensions: quantity and quality, each comprising two indicators. The quantity dimension measures how many people wish to work (labor force participation) and how many are actually employed (employment rate). The quality dimension assesses how much of the work generated is registered in social security systems (formality) and how many workers earn wages sufficient to lift them above the poverty line (sufficient wages). Through the Better Jobs Index, the Inter-American Development Bank aims to provide countries with a new instrument to more effectively monitor employment conditions, facilitate cross-country comparisons, and promote policies that lead to more favorable employment conditions.

The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

Part Time Employment in the United States decreased to 28190 Thousand in June from 28557 Thousand in May of 2025. This dataset provides - United States Part Time Employment- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context

This dataset was created by our in-house Web Scraping and Data Mining teams at PromptCloud and DataStock. You can download the full dataset here. This sample contains 30K records. You can download the full dataset here

Content

Total Records Count: 838451 Domain Name: monster.usa.com Date Range: 01st Jul 2020 - 30th Sep 2020 File Extension: ldjson

Available Fields: uniq_id, crawl_timestamp, url, job_title, category, company_name, country, post_date, job_description, job_board, geo, html_job_description, test1_countries, site_name, domain, postdate_yyyymmdd, predicted_language, test1_inferred_city, test1_inferred_state, test1_inferred_country, inferred_city, inferred_state, inferred_country, has_expired, last_expiry_check_date, latest_expiry_check_date, duplicate_status, dataset, is_remote, postdate_in_indexname_format, fitness_score

Acknowledgements

We wouldn't be here without the help of our in house web scraping and data mining teams at PromptCloud and DataStock.

Inspiration

This dataset was created keeping in mind our data scientists and researchers across the world.

United States US: Employment To Population Ratio: National Estimate: Aged 15-24 data was reported at 50.340 % in 2017. This records an increase from the previous number of 49.410 % for 2016. United States US: Employment To Population Ratio: National Estimate: Aged 15-24 data is updated yearly, averaging 54.810 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 61.150 % in 1989 and a record low of 45.000 % in 2010. United States US: Employment To Population Ratio: National Estimate: Aged 15-24 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 to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Full Time Employment in the United States increased to 135277 Thousand in June from 134840 Thousand in May of 2025. This dataset provides - United States Full Time Employment- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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/

This dataset provides valuable insights into the US data science job market, containing detailed job listings scraped from the Indeed web portal on 20th November 2022. It is ideal for those seeking to understand job trends, analyse salary expectations, or develop skills in data analysis, machine learning, and natural language processing. The dataset's purpose is to offer a snapshot of available positions across various data science roles, including data scientists, machine learning engineers, and business analysts. It serves as a rich resource for exploratory data analysis, feature engineering, and predictive modelling tasks.

Columns

• Title: The job title of the listed position.
• Company: The hiring company posting the job.
• Location: The geographic location of the job within the US.
• Rating: The rating associated with the job or company.
• Date: Indicates how long the job had been posted prior to 20th November 2022.
• Salary: The salary information provided in US Dollars ($). Please note that many entries in this column may be missing as salary details are often not disclosed in job listings.
• Description: A brief summary description of the job.
• Links: The direct link to the original job posting on the Indeed platform.
• Descriptions: The full-length description of the job, encompassing all details found in the complete job posting.

Distribution

This dataset is provided as a single data file, typically in CSV format. It comprises 1200 rows (records) and 9 distinct columns. The file name is data_science_jobs_indeed_us.csv.

Usage

This dataset is perfectly suited for a variety of analytical tasks and applications: * Data Cleaning and Preparation: Practise handling missing values, especially in the 'Salary' column. * Exploratory Data Analysis (EDA): Discover trends in job titles, company types, and locations. * Feature Engineering: Extract new features from the 'Descriptions' column, such as required skills, education levels, or experience. * Classification and Clustering: Develop models for salary prediction, or perform skill clustering analysis to guide curriculum development. * Text Processing and Natural Language Processing (NLP): Analyse job descriptions to identify common skill demands or industry buzzwords.

Coverage

The dataset's geographic scope is limited to job postings within the United States. All data was collected on 20th November 2022, with the 'Date' column providing information on how long each job had been active before this date. The dataset covers a wide range of data science positions, including roles such as data scientist, machine learning engineer, data engineer, business analyst, and data science manager. It is important to note the presence of many missing entries in the 'Salary' column, reflecting common data availability challenges in job listings.

License

CCO

Who Can Use It

This dataset is an excellent resource for: * Aspiring Data Scientists and Machine Learning Engineers: To sharpen their data cleaning, EDA, and model deployment skills. * Educators and Curriculum Developers: To inform and guide the development of relevant data science and analytics courses based on real-world job market demands. * Job Seekers: To understand the current landscape of data science roles, required skills, and potential salary ranges. * Researchers and Analysts: To glean insights into labour market trends in the data science domain. * Human Resources Professionals: To benchmark job roles, skill requirements, and compensation within the industry.

Dataset Name Suggestions

• Indeed US Data Science Job Insights
• US Data Science Job Market Analysis
• Data Professional Job Postings (Indeed USA)
• Data Science Career Opportunities (USA)

Attributes

Original Data Source: Data Science Job Postings (Indeed USA)

The dataset consists of data from relevant companies and industries' job postings. The dataset includes unique job and company-level attributes and identifiers, such as job title, full job description, job URL, company name, location, job type (full-time/ part-time), salary, and more. The data can be provided hourly, daily, weekly, bi-weekly, monthly, or one-time, depending on the client's requirements.

A. Usecase/Applications possible with the data:

• Build a fuller picture of companies' strategic moves.
• Provide almost real-time data about job postings.
• Enable a data-driven decision-making strategy for hiring.
• Building a talent pool.

How it works?

• Analyze sample data
• Customize parameters to suit your needs
• Add to your projects
• Contact support for further customization

Workforce Individual Performance Record Data: The Workforce Individual Performance Record Data is data ETA collects from grantees on a quarterly basis via form ETA-9172 (DOL Participant Individual Record Layout (PIRL)). This dataset includes information on the WIOA Title I Adult, Dislocated Worker, Youth, WIOA Title III Wagner-Peyser Employment Service, Trade Adjustment Assistance, National Dislocated Worker Grants, National Farmworker Jobs Program (Career Services and Training), National Farmworker Jobs Program (Housing), Indian and Native American Program (Adult), Indian and Native American Program (Youth), Reentry Employment Opportunities (REO) (Adult), Reentry Employment Opportunities (REO) (Youth), YouthBuild, H-1B, Job Corps, Senior Community Service Employment Program (SCSEP), Registered Apprenticeship Grants Program, and the Veteran’s Employment Service’s Jobs for Veterans State Grant programs for performance accountability purposes. The participant individual record data include data on the individual's characteristics, types of services received, and outcomes attained as a result of participating in the program for each of these programs. The individual records from programs with state grantees include Wage Data provided by state UI Offices and through the SWIS Agreement. For some of these programs, data is available in aggregate and modified public use files on ETA’s website (https://www.dol.gov/agencies/eta/performance/results/national).

Context

This dataset was created by our in-house Web Scraping and Data Mining teams at PromptCloud and DataStock. You can download the full dataset here. This sample contains 30K records. You can download the full dataset here

Content

Total Records Count : 3933743  Domain Name : indeed.usa  Date Range : 01st Apr 2021 - 30th Jun 2021   File Extension : ldjson

Available Fields : uniq_id, crawl_timestamp, url, job_title, category, company_name, city, state, country, post_date, job_description, job_type, apply_url, job_board, geo, job_post_lang, inferred_iso2_lang_code, is_remote, test1_cities, test1_states, test1_countries, site_name, html_job_description, domain, postdate_yyyymmdd, predicted_language, inferred_iso3_lang_code, test1_inferred_city, test1_inferred_state, test1_inferred_country, inferred_city, inferred_state, inferred_country, has_expired, last_expiry_check_date, latest_expiry_check_date, dataset, postdate_in_indexname_format, segment_name, duplicate_status, fitness_score  

Acknowledgements

We wouldn't be here without the help of our in house web scraping and data mining teams at PromptCloud, DataStock and live job data from JobsPikr.

Inspiration

This dataset was created keeping in mind our data scientists and researchers across the world.