Dataset

healthcare-job-postings-data-from-emedcareers

Jobs & Workforce Download 1 source

This dataset contains 40,000 latest job postings in Europe from eMedCareers.

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Dataset card

healthcare-job-postings-data-from-emedcareers is listed on Kaggle by PromptCloudHQ.

The listing has drawn 659 downloads and 13 likes on Kaggle.

The data

The source tags it with europe, healthcare and business.

Documentation & references 1
  1. PromptCloudHQ/healthcare-job-postings-data-from-emedcareers: listing on Kaggle

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 sourcesFree alternative data sources for filings, hiring, economic history, satellite imagery and web research, with access details and commercial-use limits.
  • 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 providersCompare job-posting APIs, free hiring indexes and official labour statistics. Learn what each measures and how to test coverage, duplicates and historical timing.
  • Alternative data pricing: costs and comparisonCompare free sources, API credits and bulk data licences. Work out total cost using published pricing examples and a practical vendor-quote worksheet.
  • Point-in-time data: avoiding look-ahead biasPoint-in-time data preserves what was available at a past decision date. Learn to handle revisions, delayed records and historical joins with worked examples.

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