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Global Job and Employer Details Repository
Data Science and Analytics
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About
Data detailing job postings scraped from indeed.com. It was produced by the PromptCloud and DataStock teams to inspire data scientists and analysts in their projects. This product offers a rich, structured view of the labour market, including job specifications, salary details, and extensive contact and geographical information for the employing companies.
Columns (List and describe each column found in the 'Original Data Sample'.)
- Job Title: The official name of the open employment position.
- Job Description: A detailed written summary of the role's responsibilities and requirements.
- Job Type: Classification indicating the employment arrangement, such as full-time or part-time.
- Categories: Tags or industrial classifications associated with the type of work.
- Location: General text description of the job's placement.
- City: The specific city where the job is situated.
- State: The state or province where the job is situated.
- Country: The country where the job is situated.
- Zip Code: The postal code for the job location.
- Address: The full street address of the job location.
- Salary From: The lower boundary of the advertised pay range.
- Salary To: The upper boundary of the advertised pay range.
- Salary Period: Indicates the frequency of the pay (e.g., annually, hourly).
- Apply Url: The direct web link to submit an application.
- Apply Email: The email address provided for application submission.
- Employees: Information concerning the estimated size of the hiring company.
- Industry: The sector in which the hiring company operates.
- Company Name: The name of the organisation offering the employment.
- Employer Email, Employer Website, Employer Phone, Employer Logo: Various contact and branding assets for the employer.
- Company description: A short explanatory summary of the employing organisation.
- Employer Location, Employer City, Employer State, Employer Country, Employer Zip Code: Geographical details pertaining to the employer's listed headquarters or office.
- Uniq Id: A unique identifier assigned to each job posting record.
- Crawl Timestamp: The specific date and time the record was extracted.
Distribution
The data is supplied in the CSV file format. It contains a total record count of 325,946 individual job postings. The source domain for all records is indeed.com.
Usage
This product is excellent for developing and training machine learning models focused on salary prediction or job classification tasks. It supports deep labour market research, analysis of hiring trends, and benchmarking salary ranges across different geographical areas.
Coverage
The temporal scope spans three months, specifically from 1st August 2019 through to 31st October 2019. Geographic coverage is detailed, providing location specifics (country, state, city, and postal code) for both the advertised job and the associated employer, enabling granular global and local analysis.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For training predictive models and performing large-scale data analysis on employment trends.
- Market Analysts: To research economic indicators, labour demand, and salary expectations within various sectors.
- Recruitment Professionals: To identify hiring hotspots and understand the competitive landscape for talent acquisition.
- Academic Researchers: For economic studies and geographical analysis of employment patterns.
Dataset Name Suggestions
- Indeed Job Postings 2019 Autumn Snapshot
- Structured Labour Market Data Aug-Oct 2019
- Global Job and Employer Details Repository
Attributes
Original Data Source: Global Job and Employer Details Repository
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