Dataset

mintic_linkedin-job-postings

Jobs & Workforce Download 1 source

The mintic_linkedin-job-postings dataset aggregates LinkedIn job posting text into a single string column with roughly 124,000 rows. It is published on Hugging Face by user jmparejaz under an unstated license.

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Dataset card

What this dataset contains

The dataset holds LinkedIn job posting records from the US region, packaged as a single parquet file under the size category of 100K to 1M rows. Each row is stored as one string value in the linkedin_jobpost column, combining fields such as company name and job title into a free-text blob rather than separated structured columns.

Structure and fields

The schema exposes only one declared column, linkedin_jobpost, typed as a string Value. The single train split contains 123,849 rows, so downstream parsing of the embedded Company_Name and Title substrings is required to recover any structured fields. Compatible tooling listed in the dataset metadata includes datasets, pandas, polars, and mlcroissant.

How analysts use it

Because the data is text, natural language processing techniques such as keyword extraction or transformer-based classification are needed before labor-market analysis. Plausible investment-fund applications include tracking hiring intensity by employer or role to gauge sector-level growth, parsing job titles to map skill demand, and monitoring US regional workforce trends. The unstated license and modest engagement metrics (27 downloads, 1 like) suggest analysts should verify provenance and terms before drawing conclusions.

Documentation & references 1
  1. jmparejaz/mintic_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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