Description
Every day, thousands of companies and individuals turn to LinkedIn in search of talent. This dataset contains a nearly comprehensive record of 124,000+ job postings listed in 2023 and 2024. Each individual posting contains dozens of valuable attributes for both postings and companies , including the title, job description, salary, location, application URL, and work-types (remote, contract, etc), in addition to separate files containing the benefits, skills, and industries associated with each posting. The majority of jobs are also linked to a company, which are all listed in another csv file containing attributes such as the company description, headquarters location, and number of employees, and follower count.**
With so many datapoints, the potential for exploration of this dataset is vast and includes exploring the highest compensated titles, companies, and locations; predicting salaries/benefits through NLP; and examining how industries and companies vary through their internship offerings and benefits. Future updates will permit further exploration into time-based trends, including company growth, prevalence of remote jobs, and demand of individual job titles over time.
Files
postings.csv
- job_id : The job ID as defined by LinkedIn (https://www.linkedin.com/jobs/view/ job_id )
- company_id : Identifier for the company associated with the job posting (maps to companies.csv)
- title : Job title.
- description : Job description.
- max_salary : Maximum salary** **
- med_salary : Median salary** **
- min_salary : Minimum salary** **
- pay_period : Pay period for salary (Hourly, Monthly, Yearly)
- formatted_work_type : Type of work (Fulltime, Parttime, Contract)
- location : Job location
- applies : Number of applications that have been submitted
- original_listed_time : Original time the job was listed
- remote_allowed : Whether job permits remote work
- views : Number of times the job posting has been viewed
- job_posting_url : URL to the job posting on a platform** **
- application_url : URL where applications can be submitted
- application_type : Type of application process (offsite, complex/simple onsite)
- expiry : Expiration date or time for the job listing
- closed_time : Time to close job listing
- formatted_experience_level : Job experience level (entry, associate, executive, etc)
- skills_desc : Description detailing required skills for job
- listed_time : Time when the job was listed
- posting_domain : Domain of the website with application
- sponsored : Whether the job listing is sponsored or promoted.
- work_type : Type of work associated with the job
- currency : Currency in which the salary is provided.
- compensation_type : Type of compensation for the job.
jobs/benefits.csv
- job_id : The job ID
- type : Type of benefit provided (401K, Medical Insurance, etc)
- inferred : Whether the benefit was explicitly tagged or inferred through text by LinkedIn
companies/companies.csv
- company_id : The company ID as defined by LinkedIn
- name : Company name
- description : Company description
- company_size : Company grouping based on number of employees (0 Smallest - 7 Largest)
- country : Country of company headquarters.
- state : State of company headquarters.
- city : City of company headquarters.
- zip_code : ZIP code of company's headquarters.
- address : Address of company's headquarters
- url : Link to company's LinkedIn page
companies/employee_counts.csv
- company_id : The company ID
- employee_count : Number of employees at company
- follower_count : Number of company followers on LinkedIn
- time_recorded : Unix time of data collection
If you find this dataset helpful, your upvote would convince me I didn't waste my summer break 😁