Resume Screening API — Parse + Score 200 Applicants Fast [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-screening-api&utm_content=nav) 1. [Home](https://resumeparser.pro) 2. Automate Resume Screening With Two API Calls Automate Resume Screening With Two API Calls ============================================ Screening is not one problem — it is two. First turn every resume into data, then rank that data against the job. Each has a dedicated endpoint; wired together they replace the recruiter's least favourite afternoon. [Get a free API key](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-screening-api&utm_content=hero) [See the HR Tech suite](https://sharpapi.com/en/solutions/hr-tech?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-screening-api&utm_content=hero-suite) 14-day trial · 100,000 words included · No credit card A resume screening API automates the first review pass over an applicant pool: extract each candidate's data, score it against the job description, and return a ranked shortlist with reasons. SharpAPI implements this as two composable endpoints — parse\_resume and resume\_job\_match\_score. The screening loop, end to end ------------------------------ The pattern is the same whether the pool holds 20 applicants or 2,000, and because both endpoints are async, the whole pool runs in parallel: Pseudocode — screen an applicant pool ``` for each application in pool: job = POST /hr/resume_job_match_score # file + job description scores[application] = poll(job.status_url) # 20 dimensions + reasons shortlist = sort(scores, by="overall_match", desc) # recruiters start at the top review(shortlist[:10].explanations) # written evidence per score ``` Need the structured profile too — for the candidate record, search, or dedupe? Run parse\_resume on the same file and store the [50+ field JSON](https://resumeparser.pro/resume-to-json) alongside the scores. What separates screening from keyword filtering ----------------------------------------------- Keyword filters reject the developer who wrote “built REST services in Django” for a “Python backend” role. Semantic scoring reads meaning: the [match-score endpoint](https://resumeparser.pro/resume-job-match-score-api) evaluates 20 dimensions of fit, weights must-haves at 3× nice-to-haves, and explains each headline number in writing. The difference is measured in good candidates that stop falling through — more in [semantic vs keyword matching](https://resumeparser.pro/guides/semantic-vs-keyword-matching). Screening you can put in front of a regulator --------------------------------------------- Automated screening is exactly what NYC Local Law 144 and the EU AI Act regulate. Two properties of this pipeline do the heavy lifting: PII never reaches the scoring model — names, ages, nationalities and photos are stripped after parsing — and every score ships with a written explanation. Ranked, and defensible. The compliance details live in [our AI screening law guide](https://resumeparser.pro/guides/ai-resume-screening-compliance). Sizing the workload ------------------- Typical screening scenarios · both endpoints ScenarioCallsPattern New job posting, 200 applicants 200 Batch-submit match-score jobs, webhook per result, sort by overall\_match Staffing bench × new client brief 1/candidate Bench resumes are already parsed; score stored profiles against the brief text Legacy database migration 10k+ Bulk parse\_resume first (see the [bulk parsing guide](https://resumeparser.pro/guides/bulk-resume-parsing)), then score on demand later Job board “fit badge” 1/apply Score at application time; show the badge, store the explanations Replace the pile with a pipeline -------------------------------- One API key covers both endpoints. Parse the pool, score it against the job, and hand your recruiters a shortlist with reasons — this week, not this quarter. [Get a free API key](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-screening-api&utm_content=footer-cta) [See the Match Score API](https://sharpapi.com/en/resume-job-match-score-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-screening-api&utm_content=footer-cta-match) 14-day trial · 100,000 words included · No credit card · 30-day money-back guarantee Questions, answered ------------------- What is a resume screening API?An API that automates the first pass over an applicant pool: it converts each resume into structured data, scores it against the job description, and returns a ranked list — so recruiters open a shortlist instead of a pile of PDFs. How do I rank 200 applicants with it?Loop the pool through the match-score endpoint — each call takes the resume file and the job description and comes back with 20 scores. Sort by overall\_match, review the explanations for the top of the list, done. The async design means all 200 jobs run in parallel. Can I control what the screening prioritizes?Yes — the context parameter accepts up to 5,000 characters of instructions: emphasize a must-have certification, de-emphasize location, credit adjacent experience. The weighting adjusts and the explanations reflect your criteria. Is automated resume screening legal?Increasingly regulated, yes — NYC Local Law 144 requires bias audits and the EU AI Act classifies hiring AI as high-risk. Two design choices here help: PII is stripped before scoring, and every score carries a written explanation a recruiter or auditor can review. 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. - [Resume Job Match Score API — 20 Scored Dimensions, 0-100](https://resumeparser.pro/resume-job-match-score-api) Send a CV file plus a job description, get a 0-100 match score across 20 dimensions with plain-language explanations. Rankable, defensible, async REST. - [Bulk Resume Parsing: 10,000 Legacy CVs Without a Meltdown](https://resumeparser.pro/guides/bulk-resume-parsing) Turn a folder of 10,000 legacy CVs into a searchable candidate database: async job queues, webhooks, rate strategy, dedupe and cost estimation. - [Semantic vs Keyword Matching in Recruiting: What Wins?](https://resumeparser.pro/guides/semantic-vs-keyword-matching) Keyword matching misses the developer who wrote "built REST services in Django". How semantic scoring reads meaning, and where keywords still help. 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-screening-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-screening-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-screening-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-screening-api.md, optimized for AI and LLM tools.