AI Scoring Weights & Calibration

XeCubes parses candidate profiles, evaluates interview transcripts, and generates a multi-factor suitability coefficient ranging from 0.0 to 100.0.

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Default Factor Weights

The holistic suitability score is aggregated using the following calibrated weight breakdown:

Skill Matching

30%

Technology overlap, programming language proficiency, framework experience, and library mastery matching the job requirement specification.

Experience History

30%

Total years of work experience, title seniority progression, leadership tenure, and historical role scope alignment.

Education Alignment

20%

Relevance of academic degrees (Computer Science, Data Science, etc.), university pedigree, and specialized professional certifications.

Culture Suitability

20%

Alignment with company working style, autonomy preferences, collaboration patterns, and team operating values.

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Calibrating Weights for Custom Roles

Enterprise teams can customize scoring weights per pipeline to prioritize specific attributes (e.g., placing 50% weight on technical skills for Staff Software Engineers):

{
  "pipeline_id": "senior-eng-pipeline",
  "scoring_weights": {
    "skill_match": 0.50,
    "experience_depth": 0.25,
    "education_alignment": 0.10,
    "culture_fit": 0.15
  },
  "pass_threshold": 80.0
}