Description
80% of resumes filtered out by ATS before human review due to keyword mismatch. Tool should analyze job description, identify critical ATS keywords, and suggest resume modifications to increase pass-through rate.
Current Impact: High-quality candidates rejected by ATS due to keyword formatting; users frustrated.
Expected Business Value: 80% improvement in ATS pass-through rate, 2x job application success, significant user value.
Steps to Reproduce
- Upload resume and target job description
- Check for ATS optimization guidance
- Observe: no analysis provided; user unaware of keyword gaps
Environment Information
- Python 3.8+
- NLP processing available
- Job description in text/PDF format
Expected Behavior
- Analyzes job description for key phrases and requirements
- Compares against resume content
- Identifies missing ATS keywords
- Suggests bullet-point rewrites incorporating keywords
- Shows ATS score (estimated pass-through likelihood)
- Provides before/after comparison
Actual Behavior
- No ATS analysis functionality
- User unaware if resume matches ATS requirements
- No optimization suggestions
- High rejection rate from automated systems
Screenshots or Recordings
Not applicable - feature missing
Additional Context
Affected Users: All job seekers; critical for career success in automated hiring.
Root Cause: No ATS keyword extraction or matching logic.
Proposed Solution: Implement keyword extraction from job description, matching against resume, with suggestion engine.
Implementation Steps:
- Extract keywords from job description using TF-IDF
- Match keywords against resume content
- Calculate ATS compatibility score (0-100)
- Generate suggestions for missing keywords
- Implement resume-rewriting suggestions
- Create ATS simulator showing filter simulation
- Expose API: POST /ats-optimize with score and suggestions
Test Cases:
- Job description with 15 keywords matched to resume (expect 10 found, 5 suggestions)
- Different resume formats (PDF, DOCX, TXT) processed correctly
- ATS score >80 for well-matched resume
- Suggestions improve score by 20+ points
- Before/after examples clear and actionable
- Performance: analyze job + resume <3 seconds
Severity: High - critical for user success
Expected Points: 500-600 GSSoC points
Suggested Labels
enhancement, ats-optimization, resume-enhancement, job-search, nlp, GSSoC26
Description
80% of resumes filtered out by ATS before human review due to keyword mismatch. Tool should analyze job description, identify critical ATS keywords, and suggest resume modifications to increase pass-through rate.
Current Impact: High-quality candidates rejected by ATS due to keyword formatting; users frustrated.
Expected Business Value: 80% improvement in ATS pass-through rate, 2x job application success, significant user value.
Steps to Reproduce
Environment Information
Expected Behavior
Actual Behavior
Screenshots or Recordings
Not applicable - feature missing
Additional Context
Affected Users: All job seekers; critical for career success in automated hiring.
Root Cause: No ATS keyword extraction or matching logic.
Proposed Solution: Implement keyword extraction from job description, matching against resume, with suggestion engine.
Implementation Steps:
Test Cases:
Severity: High - critical for user success
Expected Points: 500-600 GSSoC points
Suggested Labels
enhancement, ats-optimization, resume-enhancement, job-search, nlp, GSSoC26