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Implement ATS (Applicant Tracking System) keyword optimization with resume enhancement suggestions #83

Description

@anshul23102

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

  1. Upload resume and target job description
  2. Check for ATS optimization guidance
  3. 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:

  1. Extract keywords from job description using TF-IDF
  2. Match keywords against resume content
  3. Calculate ATS compatibility score (0-100)
  4. Generate suggestions for missing keywords
  5. Implement resume-rewriting suggestions
  6. Create ATS simulator showing filter simulation
  7. 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

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