12d • General Discussion
n8n Resume Parser That Eliminated 200 Hours Annual Manual Screening 🔥
Recruiting resume screening. 480 submissions annually. Manual review consuming 200 hours.
Built n8n workflow. Zero manual reading. Systematic scoring.
THE RECRUITING PROBLEM:
Every resume requiring manual processing. Recruiter downloads document from email or applicant tracking system. Reads entire resume completely - work history, education, skills sections. Manually notes years of experience, education level, technical skills mentioned.
Calculates total years of experience manually by reading job dates. Assigns qualification score subjectively based on recruiter judgment.
25 minutes per resume. 480 submissions annually = 200 hours consumed.
Quality audit revealed 18.7% error rate across all resume reviews. Inconsistent scoring between recruiters. Manual calculation mistakes counting experience years. Strong candidates overlooked during rush periods. Incomplete database entries missing contact information.
THE n8n AUTOMATION:
8-node workflow with automatic scoring:
Node 1 - Google Drive Trigger: Monitors resume folder
Node 2 - Download Resume: Retrieves document
Node 3 - Parse Resume: Extracts candidate data
Node 4 - Score Candidate: Calculates experience, education, skills scores
Node 5 - Merge Binary: Combines metrics with document
Node 6 - AI Assessment: Generates candidate evaluation
Node 7 - Log Database: Updates tracking spreadsheet
Node 8 - Notify Team: Alerts recruiters via Slack
EXTRACTION:
Personal - name, email, phone, location, LinkedIn
Experience - company, position, dates, achievements
Education - institution, degree, field, graduation date
Skills - technical skills, soft skills, languages
Additional - certifications, summary
SCORING LOGIC: ( javascript )
// Experience (40 points max)
if (years >= 5) score += 40;
else if (years >= 2) score += 25;
else score += 10;
// Education (30 points max)
if (degree === 'PhD') score += 30;
else if (degree === 'Master') score += 25;
else if (degree === 'Bachelor') score += 20;
// Skills match (30 points max)
requiredSkills.forEach(skill => {
if (candidateSkills.includes(skill)) {
score += 3; // max 30
}
});
Status determination - 75+ = Strong Candidate, 50-74 = Potential, <50 = Not a Match.
12-MONTH RESULTS:
480 resumes processed. Zero manual screening. Zero calculation errors. Zero scoring inconsistencies.
Consistency - 100%. Same qualifications scored identically across all reviewers.
Time recovered - 200 hours annually. Reallocated from manual resume screening to direct candidate engagement and interview coordination.
Templates: n8n
How many hours screening resumes? What's your scoring consistency rate?
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n8n Resume Parser That Eliminated 200 Hours Annual Manual Screening 🔥
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