Methodology

Last data update: 2026-06-27.

Two layers of data

We combine a listed-company layer (postings from major public companies' own career sites) with a national labour-market layer (every public job ad in a country, from its public employment service). The first shows what listed firms hire for directly; the second reveals the whole market around them — including the staffing agencies they recruit through.

Collection — listed companies

For each company we identify the applicant-tracking system (ATS) powering its career site — e.g. Workday, SuccessFactors, Oracle, SmartRecruiters, Greenhouse, Teamtailor or Phenom — and read its public listings feed. We request data at a polite rate and store only what is needed to count and categorise openings.

Collection — national labour markets

We also ingest every public job ad from each country's employment service: Arbetsförmedlingen (Sweden), NAV / Arbeidsplassen (Norway), Työmarkkinatori (Finland) and the EU's EURES portal. Each employer is then labelled stock-listed (matched by name to a stock-exchange listing, with its ticker), public sector, staffing agency or private.

Coverage by country: Sweden and Norway are captured in full; Finland is near-complete (~85%, limited by the EURES paging window); Denmark is the EURES-listed subset (its national Jobnet is login-gated); Germany is not yet included. Listed/private labelling matches names against Nasdaq (US and Nordic), Euronext Oslo and Xetra; close name variants of a few large firms can be missed.

Classification

Each posting is assigned a role type from its title using a multilingual keyword model (e.g. “Software & IT”, “Sales & Business Dev”, “Production & Operations”, “Healthcare & Medical”), and a country parsed from its location. Titles we cannot confidently classify — around one in ten, mostly less common languages — fall into “Other” rather than being forced into a bucket.

Updates & trends

The dataset refreshes daily. We track when a posting first appears and when it disappears, which is what powers the “total open jobs over time” trend — a true, unbiased hiring-velocity series that grows the longer the tracker runs.

The “when current openings were posted” chart is a different, narrower thing: a recency snapshot of today’s open roles by their posting date. We deliberately do not read it as acceleration — older weeks under-count roles that have already closed, so any apparent “ramp” would be a survivorship artifact rather than a real signal.

Hiring intensity

We also show open jobs per $1B of market value, benchmarked against sector peers. It surfaces structural differences — capital-intensive firms (oil majors, holding companies, banks) hire little directly and sit well below their sector, while labor-intensive services and retail sit above it. Market cap is an approximate, periodic figure.

Known limitations

• Job titles in less common languages are harder to classify and more often land in “Other” (about one in ten).
• Some career sites expose only a city, so a share of postings show an “Unknown” country.
• A minority of listed companies use career platforms without a public feed and are not yet covered.
• National coverage varies: Finland is ~85% and Denmark is a partial (EURES) subset; Germany is not yet included.
• Employer labelling is name-matched to exchange listings, so a few large firms' alternate legal names can be mislabelled.
• Counts are a point-in-time snapshot and may differ slightly from a source's own total.

Hiring Ticker publishes aggregate statistics and links back to each source. We do not republish full job descriptions.