Resume Job Match Score API — 20 Scored Dimensions, 0-100   [ResumeParser.pro](https://resumeparser.pro)

 - [Parsing API](https://resumeparser.pro/resume-parsing-api)
- [Match Score API](https://resumeparser.pro/resume-job-match-score-api)
- [Sample JSON](https://resumeparser.pro/resume-to-json)
- [Guides](https://resumeparser.pro/guides)
- [Glossary](https://resumeparser.pro/glossary)
- [Get API key](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=nav)

   1. [Home](https://resumeparser.pro)
2. Score Any Resume Against Any Job — Across 20 Dimensions

 Score Any Resume Against Any Job — Across 20 Dimensions
=======================================================

 One number can rank candidates. Twenty numbers with written reasons can defend the ranking to a recruiter, a candidate, or an auditor. That difference is the product.

 [Start scoring free](https://sharpapi.com/en/resume-job-match-score-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=hero) [Endpoint docs](https://sharpapi.com/documentation?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=hero-docs) 

14-day trial · 100,000 words included · No credit card

  The SharpAPI Resume Job Match Score API takes a resume file and a job description and returns a 0–100 score across 20 dimensions (skills, experience, education, technical stack, seniority, stability and more), each with a plain-language explanation of the evidence.

A real response, dimension by dimension
---------------------------------------

 This is the sample payload for a senior PHP developer scored against a Laravel role. Note the zeros: the resume has no education section, so the scorer says so instead of guessing.

 overall\_match 72 Weighted aggregate of all 20 dimensions 

 skills\_match 80 Strong PHP/MySQL; Laravel not mentioned explicitly 

 experience\_match 90 22 years of programming — exceeds requirements 

 education\_match 0 No education section found in the resume 

 technical\_stack\_match 80 Backend stack aligns with the posting 

 job\_title\_relevance 70 Titles adjacent to the advertised role 

 industry\_experience\_match 85 Long record in software product companies 

 language\_proficiency\_match 100 Fluent in the posting’s required language 

 management\_experience\_match 100 Led teams at the required level 

 remote\_work\_flexibility 90 Documented remote work history 

 stability\_score 85 Healthy tenure lengths, no job-hopping pattern 

 location\_preference\_match 20 Candidate is in a different region than the role 

 Sample response · 12 of 20 dimensions shown · also scored: certifications, project experience, methodologies, soft skills, location preference, training relevance, years-of-experience weighting, recency of relevant roles

How the weighting works
-----------------------

 Not all dimensions matter equally, and the rubric is public rather than secret:

- **Critical (3× weight)** — skills match, experience match, technical stack match
- **Important (2×)** — job-title relevance, industry experience, recent-role relevance, language proficiency, years-of-experience weighting
- **Standard (1×)** — the remaining eleven, from certifications to stability

 Requirements the job description marks as must-have weigh three times more than nice-to-haves. And when your pipeline knows better, say so: the context parameter takes up to 5,000 characters of plain-text instructions — emphasize a certification, de-emphasize location, credit adjacent experience — and the weighting adjusts.

The request
-----------

  POST /api/v1/hr/resume\_job\_match\_score ```
curl -X POST 'https://sharpapi.com/api/v1/hr/resume_job_match_score' \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -F 'file=@candidate.pdf' \
  -F 'content=We are hiring a Senior Backend Developer (PHP/Laravel)…' \
  -F 'language=English' \
  -F 'context=EMPHASIZE: AWS certification. DEEMPHASIZE: on-site availability.'
```

 Same async pattern as every SharpAPI endpoint: 202 Accepted, a status URL, poll or webhook. Score two candidates or two thousand — the calls run in parallel.

Scoring that survives an audit
------------------------------

 Before scoring, the pipeline strips personally identifying information from the parsed resume: name, email, phone, address, date of birth, nationality, photo and profile links. The model evaluates professional qualifications and nothing else.

 Combined with per-dimension explanations, that design maps directly onto what regulators now ask of hiring AI — bias audits under [NYC Local Law 144](https://resumeparser.pro/guides/ai-resume-screening-compliance) and transparency duties under the EU AI Act. A score you can explain is a score you can keep using.

Where teams point it
--------------------

 **ATS shortlisting** — recruiters open a ranked list, not a pile of PDFs. 200 applicants → sorted by overall\_match

 **Job boards** — show applicants a fit score before they apply; fewer spray-and-pray applications, better matches. candidate ↔ posting → fit badge

 **Staffing agencies** — match the whole candidate bench against a new client brief in one batch run. bench × brief → ranked longlist

 **Career tools** — show job seekers which requirements they miss and what to fix. gap report → coaching plan

 Screen smarter, not longer
--------------------------

Send a CV and a job description; get a 20-dimension match report with written reasons back in seconds. The trial's 100,000 words score a real applicant pool.

 [Start scoring free](https://sharpapi.com/en/resume-job-match-score-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=footer-cta) [Endpoint docs](https://sharpapi.com/documentation?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=footer-cta-docs) 

14-day trial · 100,000 words included · No credit card · 30-day money-back guarantee

 Questions, answered
-------------------

  What does the Resume Job Match Score API return?A 0-100 score for each of 20 dimensions — skills, experience, education, certifications, technical stack, job-title relevance, industry experience, soft skills, language proficiency, management experience, stability and more — plus an overall\_match weighted aggregate and plain-language explanations that name the evidence behind the key scores.

   What inputs does the API need?Two things: the resume file (PDF, DOCX, RTF, TXT or image) and the job description as plain text. Optionally add a language for the explanations and a context string of up to 5,000 characters that tells the scorer what to emphasize, de-emphasize or credit.

   How is the match score calculated?Dimensions carry weights: skills, experience and technical stack count triple; job-title relevance, industry experience, recency, language and years of experience count double; the rest count once. Requirements marked as must-have in the job description weigh three times more than nice-to-haves. Every headline score ships with a written reason, so it is never a black box.

   Can it score a resume in one language against a job ad in another?Yes. A German CV can be scored against an English job description, and the explanations come back in whichever of 80+ languages you request.

   Does the score discriminate by name, age or nationality?Personally identifying information — name, email, photo links, age, nationality, social profiles — is stripped from the parsed resume before scoring. The model evaluates professional qualifications only, which supports bias-audit requirements like NYC Local Law 144.

   What does it cost to score candidates?Per-word metered pricing from $50/month, same as all SharpAPI endpoints. The 14-day trial includes 100,000 words — enough to score a real applicant pool — with no credit card required.

   Further reading
---------------

- [Resume Parsing API — PDF, DOCX & Photo CVs to JSON (80+ Langs)](https://resumeparser.pro/resume-parsing-api) AI resume parsing API: send a PDF, DOCX, RTF, TXT or photo CV, get back 50+ structured JSON fields. 80+ languages, OCR included, async REST, from $50/mo.
- [What Is a Good Resume Match Score? 75-85% (And Why)](https://resumeparser.pro/what-is-a-good-resume-match-score) A 75-85% match score usually signals a strong candidate; 100% often signals keyword stuffing. How match scores are computed and how to read them.
- [How ATS Scores Resumes: From Keyword Match to AI Ranking](https://resumeparser.pro/how-ats-scores-resumes) What happens between resume upload and recruiter shortlist: parsing, keyword matching, knockout rules and the shift to explainable AI match scores.
- [AI Resume Screening Laws: NYC LL144 and the EU AI Act](https://resumeparser.pro/guides/ai-resume-screening-compliance) AI hiring tools face bias audits under NYC Local Law 144 and high-risk rules under the EU AI Act. Why explainable, PII-blind scoring is the safe design.

    ResumeParser.pro — a free resource on resume parsing and candidate matching, written and maintained by the team behind [SharpAPI](https://sharpapi.com/?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=footer). The APIs documented here: [Resume Parsing API](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=footer) and [Resume Job Match Score API](https://sharpapi.com/en/resume-job-match-score-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-job-match-score-api&utm_content=footer). SDKs on [GitHub](https://github.com/sharpapi).

 On this site: [What is resume parsing](https://resumeparser.pro/what-is-resume-parsing)·[How parsing works](https://resumeparser.pro/how-does-resume-parsing-work)·[Extracted fields](https://resumeparser.pro/what-fields-does-a-resume-parser-extract)·[Resume to JSON](https://resumeparser.pro/resume-to-json)·[Best parser APIs](https://resumeparser.pro/guides/best-resume-parser-apis)·[All guides](https://resumeparser.pro/guides)·[Glossary](https://resumeparser.pro/glossary)·[About](https://resumeparser.pro/about)

 No cookies, no tracking pixels, no popups. © 2026 [A2Z Web](https://a2zweb.co).

 A Markdown version of this page is available at https://resumeparser.pro/resume-job-match-score-api.md, optimized for AI and LLM tools.