Jobs dataset from careerbuilder
This powerful dataset represents a meticulously curated snapshot of the United States job market throughout 2021, sourced directly from CareerBuilder, a venerable employment website founded in 1995 with a formidable global footprint spanning the US, Canada, Europe, and Asia. It offers an unparalleled opportunity for in-depth research and strategic analysis.
Dataset Specifications:
- Source: CareerBuilder.com (US Listings)
- Crawled by: Crawl Feeds in-house team
- Volume: Over 422,000 unique job records
- Timeliness: Last crawled in May 2021, providing a critical historical benchmark for post-pandemic labor market recovery and shifts.
- Format: Compressed ZIP archive containing structured JSON files, designed for seamless integration into databases, analytical platforms, and machine learning pipelines.
- Accessibility: Published and available immediately for acquisition.
Richness of Detail (22 Comprehensive Fields):
The true analytical power of this dataset stems from its 22 granular data points per job listing, offering a multi-faceted view of each employment opportunity:
-
Core Job & Role Information:
id
: A unique, immutable identifier for each job posting.title
: The specific job role (e.g., "Software Engineer," "Marketing Manager").description
: A condensed summary of the role, responsibilities, and key requirements.raw_description
: The complete, unformatted HTML/text content of the original job posting – invaluable for advanced Natural Language Processing (NLP) and deeper textual analysis.posted_at
: The precise date and time the job was published, enabling trend analysis over daily or weekly periods.employment_type
: Clarifies the nature of the role (e.g., "Full-time," "Part-time," "Contract," "Temporary").url
: The direct link back to the original job posting on CareerBuilder, allowing for contextual validation or deeper exploration.
-
Compensation & Professional Experience:
salary
: Numeric ranges or discrete values indicating the compensation offered, crucial for salary benchmarking and compensation strategy.experience
: Specifies the level of professional experience required (e.g., "Entry-level," "Mid-senior level," "Executive").
-
Organizational & Sector Context:
company
: The name of the employer, essential for company-specific analysis, competitive intelligence, and brand reputation studies.domain
: Categorizes the job within broader industry sectors or functional areas, facilitating industry-specific talent analysis.
-
Skills & Educational Requirements:
skills
: A rich collection of keywords, phrases, or structured tags representing the specific technical, soft, or industry-specific skills sought by employers. Ideal for identifying skill gaps and emerging skill demands.education
: Outlines the minimum or preferred educational qualifications (e.g., "Bachelor's Degree," "Master's Degree," "High School Diploma").
-
Precise Geographic & Location Data:
country
: Specifies the country (United States for this dataset).region
: The state or province where the job is located.locality
: The city or town of the job.address
: The specific street address of the workplace (if provided), enabling highly localized analysis.location
: A more generalized location string often provided by the job board.postalcode
: The exact postal code, allowing for granular geographic clustering and demographic overlay.latitude
&longitude
: Geospatial coordinates for precise mapping, heatmaps, and proximity analysis.
-
Crawling Metadata:
crawled_at
: The exact timestamp when each individual record was acquired, vital for understanding data freshness and chronological analysis of changes.
Expanded Use Cases & Analytical Applications:
This comprehensive dataset empowers a wide array of research and commercial applications:
-
Deep Labor Market Trend Analysis:
- Identify the most in-demand job titles, skills, and educational backgrounds across different US regions and industries in 2021.
- Analyze month-over-month or quarter-over-quarter hiring trends to understand recovery patterns or shifts in specific sectors post-pandemic.
- Spot emerging job roles or skill combinations that gained prominence during the dataset's period.
- Assess the volume of remote vs. in-person job postings and their distribution.
-
Strategic Talent Acquisition & HR Analytics:
- Benchmark job requirements, salary ranges, and desired experience levels against market averages for specific roles.
- Optimize job descriptions by identifying common keywords and phrases used by top employers for similar positions.
- Understand the competitive landscape for talent in specific geographic areas or specialized skill sets.
- Develop data-driven recruitment strategies by identifying where and how competitors are hiring.
-
Compensation & Benefits Research:
- Conduct detailed salary analysis broken down by job title, industry, location (state, city, even postal code), experience level, and required skills.
- Identify potential salary premiums or discrepancies for niche skills or hard-to-fill roles.
- Support robust compensation planning and negotiation strategies.
-
Educational & Workforce Development Planning:
- Universities and vocational schools can align curriculum with real-world employer demand by analyzing required
skills
andeducation
fields. - Government agencies can identify areas for workforce retraining or development programs based on skill gaps revealed in job postings.
- Career counselors can advise job seekers on in-demand skills and promising career paths.
- Universities and vocational schools can align curriculum with real-world employer demand by analyzing required
-
Economic Research & Forecasting:
- Economists can use the volume and nature of job postings as a leading indicator for economic activity and regional growth.
- Analyze the impact of economic policies or global events on specific industries' hiring patterns.
- Study labor mobility and migration patterns based on job locations.
-
Competitive Intelligence for Businesses:
- Monitor the hiring activity of direct competitors or companies in adjacent markets, understanding their growth areas and talent acquisition strategies.
- Identify which specific skills or roles competitors are heavily investing in.
-
Advanced AI/ML Model Training:
- Train machine learning models for job matching algorithms (connecting candidates to relevant jobs).
- Develop NLP models for automated resume parsing and skill extraction from
raw_description
. - Create predictive models for job market trends or salary estimation.
- Build recommender systems for career pathing.
-
Geospatial Analysis & Market Mapping:
- Utilize
latitude
,longitude
,postalcode
, andaddress
to create detailed maps of job density, skill concentrations, or salary hot zones across the US. - Identify underserved regions or emerging job hubs.
- Utilize
By leveraging this meticulously crawled data, businesses, researchers, and policymakers can gain an unparalleled data-driven understanding of the dynamics and opportunities within the 2021 US job market.
Last crawled:
May 2021
Data points:
salary, domain, education, crawled_at, description, title, skills, country, raw_description, locality, posted_at, longitude, postalcode, url, experience, address, latitude, location, id, company, region, employment_type
Data points count:
22
Total Downloads
6 +
Total Views
251
Sample dataset:
Availability or Type:
Immediately
Delivery time:
immediately