What Fields Does a Resume Parser Extract? All 50+ Listed [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=what-fields-does-a-resume-parser-extract&utm_content=nav) 1. [Home](https://resumeparser.pro) 2. Every Field a Resume Parser Extracts Every Field a Resume Parser Extracts ==================================== The complete field inventory of a production resume parser — real schema field names, grouped by cluster, with the derived signals most people don't know parsing can produce. Updated 9 August 2026 · by the SharpAPI team A production resume parser extracts 50+ fields: identity and contact data, per-role work history with skills, education with normalized degrees, certifications, languages, projects, publications, licenses, plus derived signals like years of experience and management level. The tables below list the actual SharpAPI schema. Identity, contact and profiles ------------------------------ Candidate profile · scalar fields FieldContents candidate\_nameFull name as written candidate\_emailEmail address candidate\_phonePhone number(s) candidate\_address / \_city / \_countryLocation; country as ISO 3166 name candidate\_linkedin / \_github / \_twitter / \_websiteProfile and portfolio links candidate\_date\_of\_birth / \_nationalityPresent on many EU CVs; your platform decides whether to store them candidate\_language / candidate\_spoken\_languagesDocument language and declared spoken languages candidate\_summary\_objectiveThe candidate's own summary statement Work history — the array that matters most ------------------------------------------ Each entry in positions\[\] is one role with its own dated context, including up to 25 skills attached to the position where they were used rather than a single undated skill cloud: positions\[\] · one object per role FieldContents position\_name / company\_name / countryRole, employer, location start\_date / end\_dateYYYY-MM-DD; null end date = current role skills\[\]Up to 25 skills used in this specific role job\_detailsThe role description text Education, with normalized vocabularies --------------------------------------- education\_qualifications\[\] normalizes the world's degree systems into comparable values — school\_type (University, Polytechnic, College, High School, Professional training — each “or equivalent”), degree\_type (Doctorate, Master's, Bachelor's, Diploma, High School Diploma, Professional Certificate) and learning\_mode (in-person, online, hybrid, trainee programme), alongside school name, faculty, specialization, country and dates. Qualifications and extras ------------------------- - candidate\_courses\_and\_certifications\[\] — courses, certificates, professional qualifications - candidate\_honors\_and\_awards\[\] — distinctions and awards - projects\[\] — name, description, URL per project - publications\[\] — title, publisher, date, URL - volunteer\_experience\[\] — role, organization, dates, details - references\[\] — name, position, company, contact - drivers\_licenses\[\] — license categories - interests\_hobbies\[\] — as declared Derived signals — computed, not copied -------------------------------------- The most useful fields for ranking are the ones no resume states outright. The parser computes them from the document's evidence: Derived fields · computed from evidence FieldValues years\_of\_experienceTotal professional years, computed from position dates has\_management\_experience / management\_levelnone · team\_lead · manager · director\_or\_above has\_remote\_work\_experience / remote\_work\_typenone · hybrid · fully\_remote work\_authorizationWork-permit status where the document states it brief\_summaryA generated summary of the candidate approximate\_ageEstimated from graduation and career dates, and stripped before any match scoring The guarantee that makes the list usable ---------------------------------------- Every field above returns on every parse: empty when the document lacks it, never missing. That determinism is what lets you write integration code against the [sample payload](https://resumeparser.pro/resume-to-json) once and run it on a million documents. To see the fields filled with real data, the explorer on that page shows a complete unedited response. Parse your first resume today ----------------------------- Send a PDF, DOCX or photo CV to the SharpAPI Resume Parsing API and get 50+ structured JSON fields back — no models to train, no OCR vendor to add. [Start parsing free](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=what-fields-does-a-resume-parser-extract&utm_content=article-end) [Endpoint docs](https://sharpapi.com/documentation?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=what-fields-does-a-resume-parser-extract&utm_content=article-end-docs) 14-day trial · 100,000 words included · No credit card · 30-day money-back guarantee Questions, answered ------------------- How many fields does a resume parser extract?Production parsers return 50+ fields. SharpAPI's schema spans contact data, work history with per-role skills, education, certifications, languages, projects, publications, volunteer work, licenses and derived signals like years of experience and management level. Can a parser extract skills per job, not just one list?Yes — the SharpAPI schema attaches up to 25 skills to each position, so you can see what a candidate used at which job and when, rather than one undated skill cloud. What derived fields can parsing produce?Beyond literal extraction: years\_of\_experience, has\_management\_experience with a level, has\_remote\_work\_experience with a type, work\_authorization and a brief summary — signals computed from the document's evidence. What happens to fields the resume does not contain?In a deterministic schema they return empty — an empty string or array, never a missing key. Your code reads the same structure for every document. Further reading --------------- - [Resume to JSON — Explore a Real Parsed Output (50+ Fields)](https://resumeparser.pro/resume-to-json) Explore a real resume-to-JSON conversion: every field a production parser extracts, plus a full 20-dimension job match score payload. No signup needed. - [What Is Resume Parsing? The 2026 Guide for HR Tech Builders](https://resumeparser.pro/what-is-resume-parsing) Resume parsing converts CV files into structured data an ATS can search. How it works, what it extracts, accuracy limits and where AI changed the game. - [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. 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=what-fields-does-a-resume-parser-extract&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=what-fields-does-a-resume-parser-extract&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=what-fields-does-a-resume-parser-extract&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/what-fields-does-a-resume-parser-extract.md, optimized for AI and LLM tools.