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Glassdoor Salary Prediction Data
LLM Fine-Tuning Data
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Free
About
This dataset provides a collection of tech job positions and associated salaries scraped from Glassdoor.com in 2017. Its primary purpose is to enable in-depth analysis of current trends within the tech job market, including the influence of company size on salaries and other pertinent job information.
Columns
The dataset is structured across several files, featuring a variety of attributes related to job postings and potential applicant characteristics:
- job_id: A unique identifier for each job posting (Numeric).
- job_state: The state where the job is located (String).
- same_state: A binary indicator showing whether the job is in the same state as the person viewing it (String).
- age: The age of the person viewing the job (Numeric).
- python_yn: A binary indicator of whether the person viewing the job knows Python (String).
- R_yn: A binary indicator of whether the person viewing the job knows R (String).
- spark: A binary indicator of whether the person viewing the job knows Spark (String).
- aws: A binary indicator of whether the person viewing the job knows AWS (String).
- excel: A binary indicator of whether the person viewing the job knows Excel (String).
- job_simp: A simplified job title (String).
- seniority: The seniority level of the job (String).
- desc_len: The length of the job description (Numeric).
- num_comp: The number of competitors for the specific job (Numeric).
- Salary Estimate: Estimated salary range for the job.
- Job Description: The detailed text description of the job.
- Rating: The company rating.
- Company Name: The name of the hiring company.
- Location: The physical location of the job.
- Headquarters: The location of the company's headquarters.
- Size: The size of the company by number of employees.
- Founded: The year the company was founded.
- Type of ownership: The legal ownership structure of the company.
- Industry: The industry sector of the company.
- Sector: The broader economic sector of the company.
- Revenue: The company's reported revenue.
- Competitors: A list of the company's known competitors.
- hourly: A binary indicator if the salary is hourly.
- employer_provided: A binary indicator if the salary is employer-provided.
- min_salary: The minimum estimated salary for the job (Numeric).
- max_salary: The maximum estimated salary for the job (Numeric).
- avg_salary: The average estimated salary for the job (Numeric).
- company_txt: Text field for company name.
Distribution
The dataset is provided in CSV format, with
eda_data.csv being approximately 3.12 MB in size. It contains 742 records across its various files, offering detailed information for each entry.Usage
This dataset is ideal for:
- Analysing current trends based on job positions and company size within the tech industry.
- Identifying factors that significantly influence data science salaries.
- Determining states and cities that offer the highest-paying data science jobs.
- Predicting job salaries for data science positions based on job descriptions and other features.
- Investigating salary variations influenced by company size and other job-related data.
Coverage
The dataset primarily covers tech job postings from Glassdoor.com for the year 2017. Geographic coverage includes various states and cities within the United States, with notable concentrations in locations such as New York, NY and San Francisco, CA. The data offers insights into different company sizes, industries, and job seniorities.
License
**CC0 1.0 Universal (CC0 1.0) - Public Domain
Who Can Use It
This dataset is suitable for:
- Data Scientists and Machine Learning Engineers for building predictive models for salary estimation.
- HR Professionals and Recruiters seeking insights into salary benchmarks and job market trends.
- Job Seekers looking to understand salary expectations and regional variations in tech roles.
- Researchers and Analysts interested in exploring the dynamics of the tech job market.
- Students learning about data analysis, statistics, and labour market economics.
Dataset Name Suggestions
- Glassdoor Tech Job Salary Predictor
- 2017 Tech Job Market Insights
- Glassdoor Salary Prediction Data
- US Tech Job Salaries 2017
- Tech Industry Compensation Trends
Attributes
Original Data Source:Glassdoor Salary Prediction Data
QUALITY