Dataset

linkedin-job-postings

Jobs & Workforce Download 1 source

The linkedin-job-postings dataset, published by xanderios on Hugging Face, contains a single CSV table of U.S. LinkedIn job listings with about 33,000 rows. It is tagged with a MIT license on the platform, though the underlying LinkedIn terms of service place restrictions on redistribution and use.

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What this dataset contains

The file is a tabular export of LinkedIn job postings located in the United States, with a single training split of 33,246 rows. Each row corresponds to one posting and carries identifying, descriptive, compensation, location, and engagement fields. The dataset is intended for workforce and labor-market analysis rather than as an official LinkedIn product.

Structure and fields

Key columns include job_id and company_id as numeric identifiers, title and description as free text, and min_salary, med_salary, max_salary, pay_period, and currency to describe compensation. Posting context is captured by formatted_work_type, work_type, remote_allowed, location, formatted_experience_level, and skills_desc, while engagement is tracked through applies and views. Lifecycle fields include original_listed_time, listed_time, expiry, closed_time, application_type, application_url, job_posting_url, posting_domain, sponsored, and a scraped flag.

How analysts use it

Investors studying labor-market signals can monitor hiring intensity, remote-work penetration, and salary ranges by company, role, or region, using title, description, location, min_salary, med_salary, max_salary, and formatted_work_type. Time-series features such as listed_time, original_listed_time, expiry, and closed_time, combined with applies and views, support studies of posting velocity, application demand, and time-to-fill as leading indicators of corporate activity.

Documentation & references 1
  1. xanderios/linkedin-job-postings: listing on Hugging Face

Further reading

All guides
  • What is alternative data?Alternative data in investment research: what the term covers, how it differs from data format, and why provenance, timing, access and validation matter.
  • Job postings as an investment signalWhy hiring data predicts fundamentals: growth intent, expansion geography, technology adoption and cost control, how postings are collected, structured and turned into tradeable indicators.
  • Web scraping and compliance in alternative dataHow scraped datasets are actually collected, where terms of service and computer-muse laws draw lines, what hiQ v. LinkedIn settled and did not, and the diligence checklist for legally fragile data.
  • Free alternative data sourcesThe practical list of free alternative-data sources for investors: public filings, official statistics, satellite and earth observation, on-chain data, web archives and open registries, what each covers, what it costs in engineering effort, and where free data falls short.
  • Alternative data for investingHow funds turn alternative data into an investment edge: signal families, evaluation, backtesting, compliance and the build-vs-buy decision, mapped to the datasets and providers indexed on this encyclopedia.
  • Job market data: datasets and providersThe datasets and providers behind labor-market signals: job postings, payroll, employee profiles and job-change data, what each source measures, its caveats and how to choose one.

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