Every field.
Every listing.
Structured.
Automatically standardise job titles, salaries, locations, skills, seniority, and metadata before any job reaches your platform.
<div class="job-listing-raw">
<h3>Senior ML Engineer ($180k–$230k)</h3>
<span class="loc">Austin, TX (Hybrid)</span>
</div>Raw job data is broken. And it's bigger than you think.
Incomplete data drives job seekers away
Missing salary. Vague locations. Unstandardised titles. Job seekers filter by all three, and when the fields are empty, the listing gets skipped.
Inconsistent titles break your search
“Sr Dev”, “Senior Developer”, and “Senior Software Engineer” are the same role. To your search engine, they are three different jobs. That’s the gap enrichment closes.
Manual enrichment doesn’t scale
Cleaning data by hand works at a hundred listings. At a hundred thousand, it breaks. Inconsistencies multiply faster than any team can fix them.
Every raw field. Enriched, standardised, and delivered automatically.
An automated four-stage enrichment engine that reads incoming raw records, standardises taxonomies, fills missing attributes, and delivers production-ready structured data.
Parse & Structure Job Data
More Data. More Context. More Value. From Every Job.
1. Job title normalisation
“Sr Dev”, “Sr. Software Eng”, and “Senior Developer” normalised to one consistent taxonomy. Every title searchable, filterable, and comparable across your entire listing inventory.
2. Salary estimation
Pay ranges estimated for the 70% of job postings that arrive without salary data, using role type, seniority, location, and industry benchmarks. Job seekers can finally filter by pay.
3. Skills extraction (NLP)
Required and preferred skills pulled from free-text descriptions automatically. Structured, tagged, and searchable, without a human reading a single job description.
4. Location geocoding
“Remote, US” becomes “United States”. “NYC area” becomes structured city, region, country, and coordinates. Every listing filterable by accurate location radius.
5. Employment type classification
Full-time, part-time, contract, remote, hybrid, standardised across inconsistent employer naming conventions. One taxonomy, applied to every record.
6. Job description parser
Propellum’s job description parser reads unstructured job description text and extracts structured fields, responsibilities, required skills, experience level, benefits. Everything a job seeker needs to decide, cleanly separated and searchable.
7. Deduplication engine
The same job from three different sources appears on your board once. Propellum’s deduplication engine matches records across sources, merges duplicates, and keeps your inventory clean.
8. EasyPost, job wrapping engine
Propellum’s proprietary EasyPost engine wraps enriched job data into your exact delivery schema, any format, any field mapping, any delivery method. The same job wrapping software that has been running in production since 1998.
Turn Unstructured Job Descriptions Into Structured, Searchable Data.
Job descriptions arrive in free text, paragraphs, bullet lists, and employer-specific formats. Propellum’s job description parser extracts key information, including skills, responsibilities, experience, qualifications, and benefits, and turns it into structured fields your job seekers can search and filter.
What the parser extracts:
Required skills
Pulled directly from the description, not guessed from the job title.
Experience level
Junior, mid, senior, lead, standardised across inconsistent employer phrasing.
Responsibilities
Separated cleanly from requirements and benefits.
Benefits
Healthcare, equity, remote work, flexible hours, tagged for filtering.
Seniority signals
Years of experience and management scope, parsed and classified.
Raw job data vs Propellum-enriched, what actually changes
Compare raw inbound job records with Propellum's fully enriched, standardized output across every critical attribute before it hits your board.
| Field | Raw (what arrives) | Enriched (what you deliver) |
|---|---|---|
| Job title | “Sr Full Stack Dev NYC” | Senior Full Stack Developer |
| Location | “NYC area” | New York City, NY, USA + coordinates |
| Salary | Not disclosed | $120,000–$145,000 estimated |
| Skills | Buried in description text | ReactNode.jsTypeScriptAWS |
| Employment type | “FT” | Full-time |
| Seniority | Not specified | Senior (5+ years) |
| Duplicates | 3 identical records from 3 sources | 1 clean, merged record |
Why the world’s leading job boards trust Propellum’s job data enrichment
Trained on 5B+ real job records
Propellum’s enrichment models aren’t trained on generic text. They’re trained on over one billion real job records, titles, descriptions, locations, salary signals, from 100+ countries and every industry. That training set is what makes the extraction accurate where others guess.
EasyPost, 30+ years of job wrapping
Propellum’s EasyPost engine has been structuring and delivering job data since 1998. The edge cases, the employer-specific formats, the schema variations, 25 years of production use means we have handled all of them. There is no job record our enrichment pipeline cannot process.
The clients who depend on it
LinkedIn. Monster. Viadeo. Experteer. OLX Jobs. Eightfold AI. The platforms the world’s job seekers trust get their structured data from Propellum. Propellum is the job data enrichment service for job boards that need accuracy at scale.
The honest comparison
Building your own enrichment vs using Propellum
| Feature | PROPELLUMRECOMMENDED | Build In-house | Manual data team |
|---|---|---|---|
| Time to first enriched feed | 24 Hours | 3–6 months | Weeks of setup |
| Engineering cost | Zero | NLP team required | No code, high time cost |
| Salary estimation | Included | Build ML model from scratch | Not possible at scale |
| Title normalisation | AI-powered, consistent | Define taxonomy, train models | Inconsistent, error-prone |
| Skills extraction | NLP, automatic | Custom NLP pipeline required | Manual and slow |
| Scale | Unlimited | Proportional to compute | Breaks at volume |
| Maintenance | Provider-managed | Permanent ML team commitment | Grows with listings |
| Best for | Job boards at any scale | Large ML teams, unique data | Very small catalogues |
Job data enrichment, Frequently asked questions
"Job data enrichment takes raw job posting data, as scraped from employer career pages, and fills missing fields, standardises inconsistent values, and structures each record for search and filtering. It covers title normalisation, salary estimation, skills extraction, location geocoding, and employment type classification. Propellum enriches every record automatically before it reaches your job board."
"Job wrapping is the process of structuring job data into a specific schema required by a job board or downstream destination. Propellum’s EasyPost engine has been performing job wrapping since 1998, mapping enriched job fields to any target schema, in any delivery format, at any scale. It is the final step before enriched records reach the board."
"A job description parser reads unstructured job description text and extracts structured data from it, required skills, experience level, responsibilities, benefits, and employment terms. Propellum’s job description parsing models are trained on over one billion job records, enabling accurate extraction regardless of how an employer has written the description or what format it uses."
"Propellum’s salary estimation model analyses four signals: job title and seniority level, employer industry, geographic location, and employment type. These are cross-referenced against salary data from comparable listings in the same market to generate an estimated pay range. Around 70% of global job postings arrive without salary data, Propellum estimates pay for all of them."
"Propellum’s enrichment pipeline fills or standardises: job title (normalised taxonomy), salary (estimated where absent), location (geocoded to city, region, country, and coordinates), skills (NLP-extracted from descriptions), employment type (standardised), seniority level, and benefits. Every field job seekers filter by is completed automatically, before the listing reaches your board."
See what enriched job data
looks like for your job board
Get a sample feed of real, enriched job listings from your target sources, delivered within 24 hours. Every field filled. No engineers required. No commitment.
No setup fee. No contract required to start. Feed delivered within 24 hours of your first conversation.