Job Title Normalizer — Seniority, Department & Core Title
Pricing
from $0.40 / 1,000 title normalizeds
Job Title Normalizer — Seniority, Department & Core Title
Turn messy job titles into the same columns: core title without level words, places or years; department (engineering, sales, data, people…); seniority (intern to executive); and whether the role leads people. For lead lists, pay tables and hiring counts. No scraping.
Pricing
from $0.40 / 1,000 title normalizeds
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Northbell
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Job Title Normalizer
One list says Sr. Product Manager, Payments, another says Senior PM, a third Product Manager II (Remote). To count, filter or price by role you need the same columns for every title. Give this Actor your titles — from a lead list, a CRM, an ATS export or a job feed — and get back the core title (level words, brackets, places and years removed), the department, the seniority from intern to executive, and whether the role leads people. Nothing is scraped: the Actor only reads the titles you send.
$0.50 per 1,000 titles, plus $0.01 per run.
The middle step of the northbell job data toolkit. Each step reads data you already have:
- Job Posting Parser: posting text → pay, skills, remote, visa
- Job Title Normalizer (this one): title → department, seniority, core title
Example
Input:
Output (a real run of this input):
| title | coreTitle | function | seniority | leadsPeople |
|---|---|---|---|---|
| Senior Software Engineer II (Remote) | Software Engineer | engineering | senior | false |
| Sr. Product Manager, Payments | Product Manager, Payments | product | senior | false |
| Account Executive - Enterprise | NYC | Account Executive | sales | mid | false |
| Executive Assistant to the CEO | Executive Assistant to the CEO | admin | mid | false |
| Head of People | Head of People | people | director | true |
"Executive Assistant to the CEO" is not an executive, and a product manager does not manage people — the rules know both.
Run it again and again
- On a schedule — save your input as a task and add a Schedule: whenever your lead list or ATS export changes (call it through the API). Send each run to Google Sheets, Slack or email with an integration on the task.
- In bulk — Send every title in Job titles in one call.
What you get
| Field | |
|---|---|
coreTitle | the title without level words (Senior, Sr., Junior, Staff, Principal, II, Level 2, Intern, Early Career…), text in brackets, a trailing place or work mode (- NYC, | Remote) and years (Summer 2027) |
function | one of: engineering, data, security, product, design, it, customer, sales, marketing, finance, people, legal, operations, executive, admin, healthcare, education, manufacturing, hospitality — or null when none fits |
seniority | intern, entry, mid, senior, lead, manager, director or executive — the same words as every northbell job scraper, so you can join the two |
leadsPeople | true for manager, director and executive titles; product, account, program and other "managers" who do not manage people are false |
Unknown is null, never a guess. A title that matches no department (Cards Experience Guide) gets function: null, not "other". The rules are written for English titles; titles in other languages get a seniority when they use common level words, and a department only when an English word matches.
Use it for
- Lead lists — keep the director-and-above people in sales or engineering
- Pay tables — group salaries by department and level instead of by thousands of spellings
- Hiring counts — how many open roles each company has per department
Input
titles: one title per line. Through the API you can also send {"id": "...", "title": "..."} objects to keep your own ids. Up to 50,000 per run.
Pricing
$0.50 per 1,000 titles, plus $0.01 per run.
For AI agents
Call with {"titles": ["Sr. Product Manager, Payments"]} — about a second. Each row has type: "title".
Related
Pay, skills, remote and visa from whole job postings: Job Posting Parser. Company headcount and growth: LinkedIn Company Scraper. Jobs with these same seniority words: Jobs API.
