How Do I Know if My Resume Parsing is Correctly Capturing Skills from Job Experience?

Ensuring that resume parsing is accurately capturing skills from job experience is crucial for correct data extraction. The Resume Parser API provides detailed information to help you verify that the skills are being captured correctly from job experience, including the source and evidence of where the skills came from.

Here’s how you can ensure that your resume parsing is working correctly:

1. Check the API Response: Breakdown of Parsed Data

The API response provides a detailed breakdown of parsed fields, such as skills, job experience, education, and more. To verify if skills from job experience are correctly captured, review the parsed skills and their corresponding fields.

Steps:

• Experience Field: Ensure the job experience section in the parsed data accurately reflects the roles and responsibilities mentioned in the resume.
• Skills Field: Verify that the skills field correctly includes all the relevant skills extracted from the job experience, such as programming languages, soft skills, or tools.

2. Review the 'Evidence' Field for Skill Sources

In the parsed data, each skill has an associated "Evidence" field that specifies the source(s) from which the skill was extracted. This helps you validate that the skills are coming from the correct sections of the resume, such as the ExperienceSection or ProjectSection.

Example of Evidence in API Response:

"SegregatedSkill": [
    {
     "Type": "SoftSkill",
     "Skill": "Troubleshooting",
     "Ontology": "Information>Computer User Support Specialists>Troubleshooting",
     "Alias": "ability to troubleshoot, Problem Troubleshooting, trouble shooter, Trouble Shooting, Trouble-Shoot, Trouble-Shooting, troubleshoot, troubleshooter, Troubleshooting Abilities, Troubleshooting Analysis, Troubleshooting Process",
     "FormattedName": "Troubleshooting",
     "Evidence": "ExperienceSection”
     "LastUsed": "June 2022",
     "ExperienceInMonths": 95
    }
]

In this example:

• The skill “Troubleshooting” is identified as a Soft Skill.
• The Evidence field shows that this skill was extracted from both the ExperienceSection of the resume.
• The LastUsed field tells you when this skill was last mentioned (June 2022).
• The ExperienceInMonths shows the duration the skill has been used (95 months).

Importance of Evidence:

• ExperienceSection: If skills are extracted from this section, it means they were mentioned in the candidate’s job roles.
• ProjectSection: Skills extracted from this section indicate the candidate’s involvement in specific projects.
• Other Sections: The Evidence field can also capture skills mentioned in other parts of the resume, ensuring comprehensive skill extraction.

3. Review Parsing Accuracy and Matching Skills

Make sure that the parsing algorithm is correctly identifying skills associated with specific job roles. For example:

• Technical Skills: If the job experience mentions Java, C++, or Python, these should be extracted as technical skills.
• Soft Skills: Skills like problem-solving, communication, and leadership should be recognized if described in the context of job experience or responsibilities.

Check for Missing or Incorrect Skills:

• Missing Skills: If certain skills explicitly mentioned in the job experience are not captured, there may be an issue with the parsing configuration or the model’s ability to identify those specific skills.
• Incorrect Skills: Ensure that the system is not misclassifying job titles or project names as skills.

Need Assistance?  

For any inquiries, please contact RChilli Support: support@rchilli.com