Jobspiq
Job Discovery
Engineering
2026-08-10 4 min read

Direct ATS Indexing vs. Job Board Noise: How Quickly Jobspiq Finds New Tech Jobs

What we measured: the median time from an employer publishing a job to Jobspiq discovering it, by source (Greenhouse about 6 minutes, Ashby about 12, Hacker News about 36), and where our listings come from.

Jobspiq Intelligence
Data Engineering & Platform Architecture
#Job Discovery#ATS Crawling#Hiring Data#Discovery Speed
Dataset Scope2,664 jobs with exact posting times (Greenhouse 107, Ashby 89, Hacker News 236, We Work Remotely 235, Himalayas 1,990; Lever excluded at n=7)
TimeframeJobs posted in the 14 days to 12 October 2026
Target GeographyIndia and remote roles open to India
Data through: 12 October 2026 (jobs posted in the last 14 days)Last updated: 2026-10-12

Executive Summary & Key Takeaways

  • Median time from an employer publishing a job to Jobspiq discovering it: about 6 minutes on Greenhouse, 12 minutes on Ashby, 36 minutes on Hacker News, 1.3 hours on We Work Remotely and 2.5 hours on Himalayas.
  • About 71% of active listings come from LinkedIn and 27% from Naukri, which publish dates but not times, so their discovery delay cannot be measured to the hour.
  • Employer career boards (Greenhouse, Workday, Ashby, Lever) are about 0.3% of listings but are the fastest sources.
  • We did not measure other job boards and make no claim about their delay or about application-timing advantages.

Correction (12 October 2026): an earlier version of this article claimed a “4x response advantage”, a “24–72 hour” aggregator delay and a chart of average hours by job board. We did not measure those, so they have been removed. This version reports only what we measured ourselves: how quickly Jobspiq discovers jobs.

For a candidate, how quickly a new job reaches them depends on how quickly it is found. Jobspiq re-crawls its sources about every 30 minutes. This article reports how fast that turns out to be in practice, where we can measure it.

Where our listings come from

Of 179,249 active listings on 12 October 2026, about 71% came from LinkedIn, 27% from Naukri, 2% from remote job boards (Himalayas, We Work Remotely, Hacker News) and 0.3% from employer career boards on Greenhouse, Workday, Ashby and Lever, plus YC. Employer ATS boards are a small share of our volume, but they are also the fastest.

How quickly we discover jobs

For jobs posted in the last 14 days, from sources that publish the exact time of posting, we compared that time with when Jobspiq first stored the job:

Median time from publication to Jobspiq discovery (hours, sources that publish timestamps)

Source: Jobspiq Job Index Data
View raw table
Greenhouse (n=107)0.1 hours
Ashby (n=89)0.2 hours
Hacker News (n=236)0.6 hours
We Work Remotely (n=235)1.3 hours
Himalayas (n=1,990)2.5 hours
  • Greenhouse: median about 6 minutes, 90% within 36 minutes (107 jobs).
  • Ashby: median about 12 minutes, 90% within 4.6 hours (89 jobs).
  • Hacker News: median about 36 minutes, 90% within 1.3 hours (236 jobs).
  • We Work Remotely: median about 1.3 hours, 90% within 1.7 hours (235 jobs).
  • Himalayas: median about 2.5 hours, 90% within 8.5 hours (1,990 jobs).

What this does not show

  • LinkedIn and Naukri are not in the chart. They provide the date a job was posted but not the time, so we cannot measure their delay to the hour.
  • We did not measure other job boards. We make no claim about how fast aggregators or other boards are, or about how much an early application helps.
  • Small samples for some sources. Lever (7 jobs) is left out. “Discovery” means the moment our crawler first stored the job.

From discovery to alert

  • De-duplication. A SHA-256 fingerprint of title, company and location merges the same job found on several sources into one listing.
  • Matching. New jobs are scored against candidate profiles about every 15 minutes.
  • Alerts. Matches above a candidate’s threshold are sent by email, Telegram, mobile push or web push. On the free plan new jobs appear after a 90-minute delay; on Pro they appear instantly (see pricing).

Direct Answers & Core Concepts

How quickly does Jobspiq discover new jobs?

For sources that publish exact posting times, the median is about 6 minutes on Greenhouse and 12 minutes on Ashby, 36 minutes on Hacker News, 1.3 hours on We Work Remotely and 2.5 hours on Himalayas (jobs posted in the 14 days to 12 October 2026). LinkedIn and Naukri publish dates only, so their delay cannot be measured to the hour.

Where do Jobspiq job listings come from?

Of 179,249 active listings on 12 October 2026, about 71% came from LinkedIn, 27% from Naukri, 2% from remote job boards and 0.3% from employer career boards (Greenhouse, Workday, Ashby, Lever) and YC.

Research Methodology & Sources

For jobs posted in the 14 days to 12 October 2026 with an exact posting time, discovery delay is the time between the posting timestamp and when Jobspiq first stored the job (its creation time). Medians and 90th percentiles are computed per source; sources with fewer than 30 jobs are left out.
Primary Data Sources
  • Jobspiq job records: posting timestamp and first-stored time
  • Active listing counts by source on 12 October 2026
Dataset Limitations: Only sources that publish a posting time can be measured. LinkedIn and Naukri, about 98% of listings, cannot. No other job board was measured, so no comparison is claimed.

Cite this Research & Open Datasets

Open Access (CC BY 4.0)

Journalists, researchers, and engineers may freely cite this dataset and findings with attribution to Jobspiq.

Jobspiq Intelligence. (2026). Direct ATS Indexing vs. Job Board Noise: How Quickly Jobspiq Finds New Tech Jobs. Jobspiq Research & Market Intelligence. https://jobspiq.in/blog/direct-ats-indexing-vs-job-board-noise
Underlying Aggregated Dataset:

Frequently Asked Questions

An applicant tracking system (ATS) is software employers use to publish and manage jobs. Reading employer boards on Greenhouse, Ashby, Lever and Workday gives the original listing and, in our measurements, the fastest discovery, but these boards are a small share of our volume.

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