What’s in the Data? (5/22)
Handling Shadow Postings
Marissa Hashizume, NLx Research Hub Economist
May 22, 2026
Welcome to the blog series, What’s in the Data? These posts will provide updates on available features and interesting discoveries in the NLx Research Hub data. Whether you’re an analyst or researcher, or just curious about what job posting data looks like, this series will keep you informed. We encourage those interested in using the NLx Research Hub data to check out our data request page for more information.
If you’ve been worried about the presence of shadow postings in the NLx Research Hub data and how they might affect your analysis, this blog post is for you! For those who aren’t familiar with the terms “shadow posting” or “shadow job” (sometimes even called “ghost jobs”), they refer to multiple postings representing the same job opening as it has the potential to hire in multiple locations. For purposes of the job feed, we need these openings to be associated with each location where they might hire, so they are replicated for geographic tagging. While this is necessary for the job feed, it can pose challenges for analysts when it’s not clear which postings are shadows.
In 2023, a shadow job flag started being coded in the daily job feed to indicate if the posting was replicated as part of the internal job feed process. While this flag is very helpful in identifying which postings are known shadows, there are a few things it cannot do, including telling us which job opening it is a shadow of and identifying shadows outside the scope of internal job feed processes.
To enhance the existing shadow job flag, we created a new approach that looks across the entire job table (i.e., all of our historical data) to identify sets of shadow postings by job title, job description, employer, date first posted in the job feed, and date most recently seen in the job feed.
This enables users to:
See which postings are shadows of the same opening for easier detection of multi-location hiring patterns
Identify shadow postings even if the employer was the one who duplicated the posting (e.g., the employer manually listed the opening in every state job bank where it could be hired)
Identify shadow postings prior to 2023 when the shadow job indicator began
As of the beginning of May 2026, we identified 132 million job posting sets in the job table. The vast majority (96%) of these sets are “singleton” postings – regular postings that are not replicates of other postings. They make up about three-quarters (74%) of the 171 million records in the job table. The remaining quarter of the job table can be grouped into sets of multi-location openings ranging from two to thousands of locations per opening. Here is a closer look at two different types of shadow sets that emerge.
Location-flexible jobs:
These are either typical remote jobs (in which case they would be tagged to every state’s capital) or jobs that can be worked at any of a specific number of locations. For example, an employer might have a few offices across the country and hires could work at any of those locations. Or, the position might be remote but need to be based in a specific region.
For truly remote postings, we would expect to see shadow job sets that are tagged to all states (50 postings in a set) or all states and territories (54 postings in a set). While the percentage of sets with 50-54 postings is very small, it is now more than 10 times as prevalent as it was pre-COVID (<0.02% of sets in 2019 vs 0.28% so far this year), which tracks with remote job opportunity trends.
Note that the shadow job fields should not be used as indicators of remote job opportunities, although there is overlap. An opening is only treated as a shadow if the employer has either duplicated it themselves, indicated multiple locations when posting, or specifically requested it be duplicated in the job feed. In other words, there are many other remote opportunities that are not duplicated into shadow postings simply because they were not obviously indicated as remote. If you’re interested in looking more at remote opportunities, keep an eye out for new remote data parsed from the job descriptions coming this summer.
Hiring multiple positions:
The other scenario that is captured in these shadow sets is an employer who is looking to hire multiple people across geographic locations, although the position is the same at each location. In this sense, these sets are not truly “shadows” of one opening but legitimately multiple openings. For example, CVS might do a batch of hiring for sales associates across multiple CVS locations. These look like a single opening because the hiring is done en masse, with each opening appearing and disappearing from the job feed on the same days and having the same employer, job title, and job description. These are the cases that are most likely to explain the sets with thousands of locations (about 1% of all postings), and also likely explain a large portion of the sets with hundreds of locations (an additional 4% of all postings).
In summary, shadow postings are complicated. How you choose to handle shadow postings in your analysis very much depends on your specific use case, but hopefully, knowing more about where they come from and how they show up in the data will help you make an informed decision. As always, please reach out to us if you have any questions or want to talk through a specific use case.
As of May 1, 2026, you can explore more about shadow postings in the job table using the new fields of shadow set ID and count of records in each shadow set. For more information on shadow postings and these new shadow set fields, please see the updated user guide, or reach out to the NLx Research Hub team if you have questions.
