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Welcome to our April 2026 release notes!

This month, we’ve got an exciting new product launch alongside some impactful data quality improvements to share.

Check it out:

• ✨ Job Posting API It's here - our brand new API for real-time access to global hiring data
• 🔧 Data Quality & Coverage Improvements: Big jumps in work email deliverability along with improved matching for location and school data across datasets.
• 🪲 Important Bug Fixes Squashed key issues to improve deduplication and consistency in our Person dataset
• 📊 Freshness Updates: This past month, we verified 68M+ jobs and detected 6M+ job changes across our global dataset

Dive into the full details below, or jump to what interests you using the table of contents below.

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Table of Contents

📣 Announcements

✨ New Products and Features

• 🆕 Beta Launch: Job Posting API

🚀 Data Updates

• Freshness
• Job Changes
• Coverage
• Commentary

🛠 Improvements and Bug Fixes

• Improvements
• Bug Fixes

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📣 Announcements

📘

Using Email Data? Check out Our New Post on Email Deliverability

Improving our Email Deliverability has been a key focus on our Data Roadmap since last October. This month, we wrote a new blog post that provides a comprehensive overview of this project and where we’re going.

If email outreach and deliverability is a key focus of yours, this post is definitely worth a read!

Building for Email Deliverability

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✨ New Products and Features

🆕 Beta Launch: Job Posting API (Docs)

What’s New

This month, we’re excited to announce the launch of our new Job Posting API to enable real-time access to complete records from our Job Posting Dataset.

The Job Posting API is a search endpoint that allows you to query and retrieve structured job posting records without needing to manage a full dataset.

With this API, you can:

• Search millions of active and historical job postings
• Filter by company, title, location, salary, and more
• Retrieve full job posting records, including raw descriptions and metadata
• Access daily-updated data sourced directly from company career pages

Why We Built This

Our goal with the Job Posting API was to provide a more flexible and accessible way to work with job posting data.

While the full Job Posting Dataset is ideal for large-scale use cases, many users need a lighter-weight, query-based solution. This API makes it easier to:

• Access only the data you need, when you need it
• Iterate on searches dynamically without managing full data pipelines
• Integrate real-time hiring data directly into applications and workflows

Key Features

• Flexible Search Options: Use simple field filters or full Elasticsearch queries for advanced use cases

• Built-in Data Cleaning: Company names, locations, and titles are normalized automatically for easier querying

• Multi-field Filtering: Combine filters across multiple attributes using AND logic

• Bulk Retrieval: Paginate and pull down all records matching your query

• Near Real-Time Data: Job postings are updated within ~24 hours of detection

📘

Check out the Docs!
To learn more and see various use cases in action, take a look at these resources:

• Job Posting API Overview
• Quickstart Guide
• Use Cases

How To Get Started

The Job Posting API is currently in beta.

To get started:

• PDL Customers: Reach out to your account team to enable access
• New to PDL? Request access here

What’s Next

This beta release is the first step in expanding how users interact with our Job Posting Data.

Over the coming months, we plan to:

• Expand data coverage and volume
• Refine the API experience and schema
• Incorporate feedback from early users to guide improvements

Have questions or suggestions? Let us know! We’re actively building this product alongside our users.

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🚀 Data Updates

Freshness

The number of jobs and locations verified in our datasets (based on the job_last_verified and location_last_updated fields).

Monthly (v33.2 → v34.0)
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 the job_last_changed field).

Monthly (v33.2 → v34.0)
Freshness updates over the past month.

Coverage (Full Stats: Person, Company, Job Posting, IP)

Monthly (v33.2 → v34.0)

Resume Dataset

API Dataset

Email Dataset

Mobile Phone Dataset

Company Dataset

Job Posting Dataset

Commentary

• Person Data
  • This month we saw a 31% increase in coverage of deliverable work_emails as a result of our ongoing work to improve our email deliverability. See improvements.
  • We saw an 11% increase in coverage for the headline field.
  • We saw a 6% drop in coverage for mobile_phones in our resume dataset this month.
• Company Data
  • We saw a decrease in the fill rate for the affiliated_profiles as a result of some improvements to this field this past month.
• Job Posting Data
  • We saw a 5% increase in the number of unique companies tracked in our Job Posting Dataset over the past month.

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🛠 Improvements and Bug Fixes

Improvements

• Email Deliverability Improvements
  • We integrated more validated emails into our data build process and improved our internal benchmarking and QA pipeline for monitoring our email deliverability
  • As a result of these changes, we saw significant increases in both coverage and deliverability this month.
  • Customers should see improvements, but should still expect some continued month-to-month variability in fill rates as this project continues
• Updated Affiliated Profile Logic
  • The affiliated_profiles field now represents a deduplicated list of all related company IDs (parent and subsidiary affiliated companies). Previously, this was capped at a max of 25 associated record IDs.
• Location Canononicalization Improvements
  • We improved location parsing and canonicalization for some specific locations, such as São Paulo, Bangalore/Bengaluru, Mexico City, and accented Brazilian city names.
  • This improves accuracy for international localities, district-style city names, and edge cases involving formatting or diacritics

Bug Fixes

• More Reliable Profile Merging
  • We fixed an issue that prevented some profiles with the same linkedin_id from merging correctly.
• School Canonicalization Reliability
  • We resolved cases where the same school raw value could map to different canonical schools.
• Names with Parenthetical Certifications
  • We fixed an issue where names containing parenthetical credentials or certifications could be parsed incorrectly, producing malformed name outputs.