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geospatial-careers/
README

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Geospatial Careers

Open intelligence layer for the people building the planet's spatial layer.

Maintained by Gerardo Ezequiel Martin Carreno. Based in London. Build-in-public on LinkedIn and at geospatial.careers.

What we publish here

Open datasets, models, and methodology for the geospatial labour market. Cross five lenses:

Demand — job postings across 35 countries and 14 official data sources
Supply — open-source library activity (GitHub releases, contributors)
Adoption — downloads from PyPI, npm, CRAN, Docker Hub, Hugging Face
Research — papers and grants from OpenAlex, arXiv, NSF, UKRI, CORDIS
Capital — funding events, M&A, IPO filings from official registries

Everything operates under a no-scraping commercial-data policy: official APIs, licensed sources, and permissive open data only.

In flight (Q2 2026)

Repo	Type	Status
`helper-seniority-v1`	model	training
`helper-title-v1`	model	training
`helper-skill-rag-v1`	model	training
`helper-salary-quantile-v1`	model	training
`champion-multi-task-v1`	model	architecture review
`champion-narrative-v1`	model	architecture review
`champion-graph-v1`	model	architecture review
`gold-seniority-2026`	dataset	annotation in progress
`state-of-geo-2026-dataset`	dataset	curation in progress

All currently private; releases land with the State of Geospatial 2026 report.

Methodology

Every claim ships with the source, the query, and the model version. Read the full methodology and verification queries at geospatial.careers/methodology when published.

Contact

Partnerships / employer enquiries: jobs@geospatial.careers
General: hello@geospatial.careers
Founder direct: me@geospatial.careers

Licence

Datasets: CDLA-Permissive-2.0 unless otherwise noted. Models: Apache 2.0 unless otherwise noted.

geospatial-careers/README