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BLUE COLLAR
JOB DATA
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SAMPLE JOB DATA

Inspect the job data,before you evaluate the vendor.

Request normalized blue-collar job records with representative fields, source context, a field dictionary and a coverage note. Samples can be scoped to the market and workflow you are considering.

Dated snapshot Visible methodology Buyer-ready sample
EVALUATION PACKAGE08 AUG 2026
REPRESENTATIVE FIELD SETFields designed for evaluation.
job_idstring

Stable normalized record identifier

titlestring

Title preserved from the source listing

companystring

Employer attached to the source

citystring

Normalized place for filtering and comparison

occupationstring

AI-assisted occupation classification

SCOPE DEFINEDSOURCE CONTEXT RETAINED
01DATED

Snapshot attached

02DEFINED

Fields and scope explained

03TRACEABLE

Source context retained

04HONEST

Limits stay visible

01 / WHY IT MATTERS

A USEFUL EVALUATION PACKAGE

Start with records your team can inspect.

A sample should answer practical buyer questions: which fields exist, how values are normalized, whether the source remains traceable and whether coverage fits the intended product or analysis.

Ask a data question

02 / EVALUATION CRITERIA

WHAT BUYERS SHOULD EXPECT

Evidence that makes the data easier to trust.

01

Representative records

Inspect normalized records rather than screenshots or marketing-only field lists.

02

Field dictionary

Understand types, definitions and whether a value is preserved, normalized, observed or enriched.

03

Source example

Follow a representative record back to the source and review its observation context.

04

Coverage note

Evaluate the sample with its market, snapshot date, source definition and known boundaries.

03 / THE DETAILS

REPRESENTATIVE FIELD SET

Fields designed for evaluation.

ITEMVALUEDEFINITION
job_idstring

Stable normalized record identifier

titlestring

Title preserved from the source listing

companystring

Employer attached to the source

citystring

Normalized place for filtering and comparison

occupationstring

AI-assisted occupation classification

first_seendate-time

First successful source observation

last_seendate-time

Most recent successful source observation

source_urlURL

Route back to the public source listing

Evaluate this with real records. Include your market, occupations and intended workflow.

Request sample records

04 / NEXT ROUTES

FROM EVIDENCE TO EVALUATION

Continue with the delivery that fits your workflow.

JOB POSTING API

Query normalized records

Explore structured job data for recruitment products, alerts and software workflows.

Explore the API page
BULK JOB DATA

Load a defined extract

Explore larger deliveries for warehouses, models, workforce analytics and research.

Explore bulk datasets

05 / FAQ

BUYER QUESTIONS

What to confirm before you use the data.

Ask about a specific market, field or delivery requirement.

[email protected]
01What does the sample package include?

The intended package includes representative normalized records, a field dictionary, a source/provenance example and a dated coverage note. Exact fields are confirmed for the requested sample.

02Can I request CSV or JSON?

Yes. State the format your team prefers when requesting the sample. Commercial delivery format and cadence are scoped separately.

03Can the sample match a specific occupation?

Include the market and occupation groups you care about. The team can then confirm whether the current coverage supports a relevant sample.

04Is the sample a live API response?

Not unless explicitly supplied through an agreed API evaluation. Static examples on the site are labelled as illustrative formats and should not be mistaken for live endpoints.

06 / NEXT STEP

START WITH A SCOPED SAMPLE

Bring us the question your data needs to answer.

Tell us your market, occupations and workflow. We will confirm whether the current coverage can support a useful evaluation before asking you to sit through a generic sales call.

EMAIL THE DATA TEAM
MARKET
Country or region
OCCUPATIONS
Trades or frontline roles
WORKFLOW
Product, analysis or research
QUESTION
What the records need to answer
[email protected]