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Australia Data Skills Intelligence - Daily Market Pulse

Under maintenance

Try for free

Your daily pulse on Australia's data job market. Scrapes Seek, Jora and LinkedIn, dedupes, then ships skill-demand rankings, co-occurrence pairs (PMI + Jaccard), community clusters, t-SNE map and per-area heatmap. One JSON powers your dashboards, reports and pricing decisions.

Pricing

from $8,000.00 / 1,000 results

Rating

0.0

(0)

Developer

data_lattice

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AU Data Skill Intelligence (Daily Auto-Refresh)

What this is for

The three Data Lattice scrapers each give you a stream of rows. This Actor consolidates and analyses them: across all ~3,000+ live AU data jobs scraped on a given day, what skills are being asked for, in what combinations, by which kinds of employers?

The output is a single ~80 KB JSON document with eight derived sections:

Section	What it answers
`top_skills`	Which skills are most demanded right now (e.g. SQL: 797 jobs)
`top_pairs`	Which skill-pairs co-occur strongest (e.g. dbt + Snowflake at PMI 2.35)
`communities`	Which skills cluster naturally (modern data stack vs classical BI)
`embedding`	2-D t-SNE coordinates for visualising the entire skill graph
`heatmap_by_area`	What % of jobs in each taxonomy area mention each skill
`n_jobs`, `n_skills`	Volume signals - how big is the dataset
`generated_at`	Snapshot timestamp so you can detect staleness
`seed` flag	True only when you've hit the cold-start fallback

How this helps you

You are a...	You use this to...
Recruitment agency	Build "what skills are most in demand for AU data engineers right now" briefs for clients in 30 seconds
Bootcamp / EdTech	Run weekly curriculum reviews - drop tools that aren't being asked for, add ones that are
Career coach	Show clients exactly which skills will move them from "applies to 100 jobs / hears nothing" to "first interview"
Salary benchmarker	Pair skill demand with the salary fields from the underlying scrapers to answer "is dbt experience worth a $10k premium?"
Data team lead	Justify your tooling choices internally: "65% of AU senior-data roles now require dbt, here's the source data"
AI / ML researcher	Track how fast the GenAI stack (LangChain, vector DBs, fine-tuning) is being absorbed into AU job descriptions

Cold-start UX

First-ever run returns a baked-in seed (~3,113 jobs, 136 skills) in 2 seconds instead of waiting 3-5 minutes for a fresh scrape. The seed is honestly labelled (seed: true, dated note) so buyers can see it's the cold-start fallback. Subsequent runs do the real refresh.

To force a fresh scrape on first run: pass force_refresh: true.

Two scheduling modes

Apify Schedules (recommended): publish the Actor and add a daily schedule in the Apify Console for 02:00 Australia/Sydney. Each run is metered as one event.
In-Docker cron (DAEMON=1): launch the container with DAEMON=1 on your own VPS / k8s. The image embeds cron + supervisord, runs an immediate refresh at boot, then re-runs every day at 02:00 AEST from inside Docker. Use this for the highest-margin path - subscribers hit your local snapshot, never Apify, so cost-of-goods is ~$0.

No personal data

The image contains the taxonomy and pipeline only. No CVs, no candidate identity. The dataset shipped is a derived market summary, never raw scraped JD content.

Pricing

$1.50 per refresh (PAY_PER_EVENT, fired as refresh_completed once per successful run). A daily subscriber pays ~$45/month metered. Three weekly runs = $18/month. You only pay when a fresh refresh actually completes.

Run it

{
  "seek_pages": 3,
  "jora_per_keyword": 12,
  "linkedin_per_keyword": 8,
  "use_seed_for_cold_start": true,
  "force_refresh": false
}

Brand

The flagship Actor of the Data Lattice portfolio. The output of this Actor is consumed downstream by the Co-Occurrence API and the RSS Feed Actors.

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