Resume Parser

Affinda's Resume Parser is the core product within the Recruitment Product Suite.

Data extracted

Affinda can return over 100 data fields from resumes. These data fields include:

Personal details

Title, first name, middle name, last name, address, contact phone, email, websites, date of birth, headshot, LinkedIn profile

Work experience

Employer, job title, location, dates employed, total years experience, occupation classification, management level

Education

Institution, degree, degree type, accreditation, year graduated

Certifications

Courses, diplomas, certificates, security clearance, and more

Skills

Individual skills (mapped to a detailed best-in-class taxonomy containing over 3,000 soft and hard skills), skill type, number of months using skills

Language(s)

Language(s) spoken, the language of the resume

Summary

Candidate summary and objective, section raw text, the probability the document is a resume

Referee details

Name, phone number

Schema

The following is an example data object returned for a resume in the API response:

  "data": {
    "name": {
      "raw": "Tim A. Smith",
      "first": "Tim",
      "last": "Smith",
      "middle": "A.",
      "title": "Dr"
    },
    "phoneNumbers": [
      "(704) 996-9966",
      "+61412632636"
    ],
    "websites": [
      "www.timsmith.com"
    ],
    "emails": [
      "[email protected]"
    ],
    "dateOfBirth": "1992-01-01",
    "location": {
      "formatted": "Blacksburg, VA, USA",
      "postalCode": "3124",
      "state": "Virginia",
      "country": "United States",
      "countryCode": "US",
      "rawInput": "Blacksburg, VA",
      "streetNumber": "1",
      "street": "Smith St",
      "apartmentNumber": "12",
      "city": "Blacksburg",
      "latitude": "67.0124",
      "longitude": "67.0124"
    },
    "objective": "",
    "languages": [
      "English",
      "French",
      "Arabic"
    ],
    "languageCodes": [
      "en",
      "fr",
      "ar"
    ],
    "summary": "",
    "totalYearsExperience": 13,
    "headShot": "string",
    "education": [
      {
        "id": 0,
        "organization": "Virginia Polytechnic Institute and State University (Virginia Tech)",
        "accreditation": {
          "education": "Bachelor of Science",
          "inputStr": "Bachelor of Science, Mechanical Engineering, expected",
          "matchStr": "Bachelor of Science",
          "educationLevel": "bachelors"
        },
        "grade": {
          "raw": "GPA : 3.35",
          "metric": "GPA",
          "value": "3.35",
          "additionalProp": {}
        },
        "location": {
          "formatted": "Blacksburg, VA, USA",
          "postalCode": "3124",
          "state": "Virginia",
          "country": "United States",
          "countryCode": "US",
          "rawInput": "Blacksburg, VA",
          "streetNumber": "1",
          "street": "Smith St",
          "apartmentNumber": "12",
          "city": "Blacksburg",
          "latitude": "67.0124",
          "longitude": "67.0124"
        },
        "dates": {
          "completionDate": "2021-05-01",
          "isCurrent": true,
          "startDate": "2019-05-01"
        }
      }
    ],
    "profession": "Software Developer",
    "linkedin": "https://www.linkedin.com/in/user-name",
    "workExperience": [
      {
        "id": 0,
        "jobTitle": "Sales and retail assistants",
        "socCode": "7111",
        "socName": "Sales and retail assistants",
        "organization": "General Motors",
        "industry": "Automotive",
        "location": {
          "formatted": "Blacksburg, VA, USA",
          "postalCode": "3124",
          "state": "Virginia",
          "country": "United States",
          "countryCode": "US",
          "rawInput": "Blacksburg, VA",
          "streetNumber": "1",
          "street": "Smith St",
          "apartmentNumber": "12",
          "city": "Blacksburg",
          "latitude": "67.0124",
          "longitude": "67.0124"
        },
        "jobDescription": "Interned with supercar Development from May 2017 to August 2017.",
        "dates": {
          "startDate": "2018-05-01",
          "endDate": "2018-08-01",
          "monthsInPosition": 0,
          "isCurrent": true
        },
        "occupation": {
          "jobTitle": "Sr. Software Developer",
          "jobTitleNormalized": "Software Developer",
          "managementLevel": "Low",
          "classification": {
            "title": "Book-keepers, payroll managers and wages clerks",
            "minorGroup": "Administrative Occupations: Finance",
            "subMajorGroup": "ADMINISTRATIVE OCCUPATIONS",
            "majorGroup": "ADMINISTRATIVE AND SECRETARIAL OCCUPATIONS",
            "socCode": 4122
          }
        }
      }
    ],
    "skills": [
      {
        "id": 0,
        "emsiId": "KS1218W78FGVPVP2KXPX",
        "name": "Applied Mechanics",
        "lastUsed": "2012-01-01",
        "numberOfMonths": 12,
        "type": "hard_skill",
        "count": 133342916,
        "weighting": 0.057699221573302296,
        "sources": [
          {
            "section": "WorkExperience",
            "position": 0,
            "workExperienceId": 1234
          }
        ]
      }
    ],
    "certifications": [
      "Certificate in AWS"
    ],
    "publications": [
      "Tim Smith et al., Investigations of nanoparticles in the pathology of the human eye, Cell 2014"
    ],
    "referees": [
      {
        "name": "Stephen Smith",
        "text": "Stephen Smith, Team Member/Mentor, Company Power Generation: [email protected]",
        "email": "[email protected]",
        "number": "+61490667215",
        "position": "Principal",
        "additionalProp": {}
      }
    ],
    "sections": [
      {
        "sectionType": "PersonalDetails",
        "bbox": [
          0,
          36.392,
          612,
          111.056
        ],
        "pageIndex": 0,
        "text": "<All text from the {sectionType} section>"
      }
    ],
    "isResumeProbability": 98,
    "rawText": "Christopher Nolan 3210 fake street '... <rest of resume text>'",
    "redactedText": "**** Objective: To obtain a job '... <rest of resume text>'",
    "additionalProp": "string"
  },

HR-XML

The data that Affinda extracts from resumes can be exported in HR-XML.

By default, our resume parser will return the data that our AI model has extracted in Affinda's own standard schema. However, users can specify that they wish to return data in HR-XML format when using the Upload a document for parsing endpoint.

Job Description Parser

Affinda's Job Description Parser uses the same technology as the Resume Parser to deliver similar data and similarly high accuracy.

Typically, the Job Description Parser is used in conjunction with the Search & Match solution to match candidates to jobs, however, it can be used standalone.

Data extracted

Job Title
Occupation Classification
Management Level
Years Experience Required
Organisation
Location
Job Contact Details (Name, Phone Number)
Start Date
Job Type (e.g. Full Time, Part Time, Casual)
Languages Required
Skills (mapped to a detailed best-in-class taxonomy containing over 3,000 soft and hard skills)
Education Level Required
Education Accreditation
Certifications
Remuneration