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Scam Job Advertisements Dataset
Fraud Detection & Risk Management
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Free
About
This dataset features a curated collection of 10,000 exclusively fake job postings, meticulously designed to aid researchers, data scientists, and analysts in investigating fraudulent recruitment trends and scam tactics. By concentrating solely on deceptive job listings, this resource enables the development and testing of machine learning models for detecting fraudulent job advertisements. It also facilitates a deeper understanding of the linguistic and structural characteristics typical of fake job adverts and helps explore the impact of such postings on job seekers and online recruitment platforms. It is particularly well-suited for analysing how scammers operate within the digital recruitment landscape and for creating tools to combat online employment scams. Please note, this dataset does not include genuine job postings and is therefore intended purely for studying fraudulent recruitment practices, not for general job market analysis.
Columns
- title: Represents the job title, with 10,000 distinct values.
- description: Provides a detailed description of the job posting, containing 10,000 unique values.
- requirements: Outlines the requirements for the job, with 971 distinct values.
- company_profile: Describes the company's profile, featuring 9,953 unique values.
- location: Specifies the job's location, with a distribution where East Rhondafurt and Brianburgh each account for 1%, and other locations make up 98% (9,753 unique locations in total).
- salary_range: Indicates the salary range, with 10,000 unique values.
- employment_type: Defines the employment type, with Part-Time and Temporary each at 20%, and other types making up 59% (5,937 unique values).
- industry: Specifies the industry sector, with Education and IT each at 13%, and other industries accounting for 74% (7,394 unique values).
- benefits: Lists any benefits offered, with Sign-on bonus at 21%, Free travel at 20%, and other benefits making up 59% (5,939 unique values).
- fraudulent: A binary label indicating whether the posting is fraudulent. All 10,000 entries in this dataset are labelled as fraudulent, with a unique value of 1.
Distribution
This dataset comprises 10,000 individual records, each representing a unique fake job posting. The data files are typically provided in CSV format. The specific number of rows or records is 10,000.
Usage
This dataset is ideal for:
- Developing and evaluating machine learning models aimed at identifying fraudulent job postings.
- Analysing the linguistic patterns and structural elements inherent in fake job advertisements.
- Investigating the broader implications of deceptive job postings on job seekers and recruitment platforms.
- Building robust tools and systems to combat online employment scams.
Coverage
The dataset has a global regional coverage. While the specific time range for the original job postings is not detailed, the dataset itself was listed on 8th June 2025. No specific demographic scope is provided.
License
CCO
Who Can Use It
This dataset is primarily intended for:
- Researchers studying online fraud and scam methodologies.
- Data Scientists focused on developing and refining fraud detection algorithms.
- Analysts interested in the characteristics and impact of fraudulent recruitment practices.
Dataset Name Suggestions
- Fake Job Postings Database
- Online Recruitment Fraud Data
- Deceptive Job Listings Repository
- Scam Job Advertisements Dataset
Attributes
Original Data Source: Fake Job Postings
QUALITY