Welcome to our May 2025 release notes!
We’ve been busy cooking up fresher data, smarter signals, and a brand-new ✨ beta to show off.
Here’s what’s new:
- 🧪 Job Posting Data (Beta): It’s here! Our new Job Posting Dataset is live in beta, and ready for work.
- 📂 New
COMPLETEDFile = Happier Pipelines: Flat file deliveries now include a top-levelCOMPLETEDfile so you can reliably trigger workflows once your dataset is ready. - 📍 Smarter, Cleaner Locations: We’ve improved how we handle tricky abbreviations like “St.” and “Mt.” (Street? Saint? Mount? Montana? We’ve got it sorted.)
- 🪄 Fresher Than Ever: This month, we verified 206M+ jobs and detected 235K+ job changes across our global dataset.
✨ New Products and Features
Beta Launch: Job Posting Data (Schema)
This month, we are thrilled to introduce our new Job Posting Dataset, now available in beta! This dataset adds a new dimension to our product offerings through insights into company hiring activity. Sourced directly from company career pages with global coverage, this dataset is an exciting complement to our Person and Company Datasets. What is it? The Job Posting Dataset is a cleaned, structured, and standardized feed of job listings pulled straight from company websites. Each record includes:- Canonicalized job titles, company information, and locations
- Posting URL and timestamps
- Full text descriptions and additional metadata
- Extract intent and other signals from information posted directly by companies themselves
- Sort, filter and segment job postings at scale
- Aggregate insights and trends across roles, companies, geographies and markets
- Leverage structured, scalable data for training AI models
- Recruiting & Talent Matching: Surface open roles, match candidates, and understand the current recruiting landscape.
- Intent-Based Sales Outreach: Identify companies hiring for key roles or specific technologies to prioritize outreach.
- Competitive & Investment Intelligence: Spot growth, expansion or strategic shifts via hiring activity across individual companies or entire markets.
- PDL Customers: Contact your account team - we can give you a walk through and set up a data evaluation.
- New to PDL? Get in touch with us - we’ll introduce you to the product and share some sample data to test with.
New: COMPLETED File for Data License Deliveries
This month, we’re making a quality of life improvement for our data license customers receiving flat file deliveries.
What’s New
We now include a COMPLETED file in your delivery bucket to signal when the entire dataset delivery is finished.
Previously, our build process generated _SUCCESS files within each subdirectory to indicate that individual data partitions had been successfully delivered. However, there was no reliable marker for when the full delivery process had completed.
With this new COMPLETED file, you can now:
- Reliably trigger your downstream ingestion or processing workflows
- Avoid premature processing based on partial data
Starting this month,
COMPLETED files will now be automatically included in the top-level directory of all flat file deliveries via:
- AWS S3
- Google Cloud Storage,
- Azure Blob Storage
_SUCCESS files will occur as we will continue to maintain the previous functionality.
If you have any questions or would like some help updating your pipeline to use this signal, please reach out to your account team!
🚀 Data Updates
Freshness
The number of jobs and locations verified in our datasets (based on thejob_last_verified and location_last_updated fields).
📌 Monthly (v30.0 → v30.1)Freshness updates over the past month.
Job Changes
The number of person records where the primary job experience changed in our Person Dataset (based on thejob_last_changed field).
📌 Monthly (v30.0 → v30.1)Freshness updates over the past month.
Coverage (Full Stats: Person, Company, IP)
📌 Monthly (v30.0 → v30.1)
Resume Dataset
API Dataset
Email Dataset
Mobile Phone Dataset
Company Dataset
Job Posting Dataset
- Coming Soon!
Commentary
📌 Monthly Highlights (v30.0 → v30.1)- Company Dataset saw a decrease in
localityandgeofields (~7%), as a result of our location cleaning improvements removing false positive matches
🛠 Improvements and Bug Fixes
Improvements
- Location Cleaning Improvements
- We improved our location cleaning and standardization processes leading to better reconciliation for
regionsand improved handling of abbreviations inlocalitynames.
- We improved our location cleaning and standardization processes leading to better reconciliation for
- Validation for
birth_dates- We added additional data validation checks to ensure that
birth_datesrepresent valid dates.
- We added additional data validation checks to ensure that
Bug Fixes
- We fixed a bug in our email deduplication process to ensure that emails with egregiously high rates of duplication are removed from our top-level fields and
emailsfield. This change impacts <1000 records. - We fixed a bug where legacy LinkedIn URLs containing encoded double-quotes (e.g.
%22) would result in 404 errors. These URLs are now removed from our top-level fields to prevent broken links. - We fixed an issue where
display_namevalues in thetop_next_employersandtop_previous_employersfields were incorrectly lowercase for API users. This issue was previously resolved for Data License customers, but this fix now applies across all delivery methods. - We updated our domain-cleaning logic to address the root cause of customer reported instances of “email-like” websites in company records. This update helps us improve our integration of non-LinkedIn website information in our Company Data build.
- We fixed a bug in our Batch Enrich tool in the API Dashboard that was failing to initiate jobs for some users. If you run into further issues, please create a support ticket.
