How a Mark-Recapture Ecology Method Exposed Silent Job Scraper Data Gaps

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A developer building a LinkedIn job-scraping tool discovered it was silently returning only about 75% of available job listings, with no error or warning in the output. The platform's pagination endpoint proved unstable, returning a different random subset of jobs on each request rather than a consistent ordered list, meaning a simple loop-until-empty approach only collected an unreliable sample. This flaw corrupted a change-tracking feature built on top, which falsely reported dozens of job openings and closures between runs just minutes apart. Standard completion heuristics — stopping after empty pages or requiring two identical passes — both failed, either firing too early or never firing at all. The developer ultimately found a reliable solution by applying the Lincoln-Petersen mark-recapture method used by ecologists to estimate population size, using overlap between two independent scrape samples to calculate total job count rather than assuming completeness.

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