cv-screener/criteria.yaml at main · HazemBZ/cv-screener · GitHub

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# ============================================================
# CV Screening Criteria Configuration
# ============================================================
# Edit this file to match your job requirements.
# Each skill/keyword has a weight (impact on overall score).
# The final score is computed as a weighted percentage 0-100.
# ============================================================

# Required skills with weights (higher = more important)
required_skills:
  python: 10
  machine learning: 8
  deep learning: 7
  nlp: 6
  computer vision: 6
  tensorflow: 5
  pytorch: 5
  docker: 4
  kubernetes: 4
  aws: 4
  git: 3
  sql: 3
  rest api: 3
  flask: 3
  django: 3
  fastapi: 3
  react: 2
  javascript: 2
  java: 2
  c++: 2

# Minimum years of experience required
min_experience_years: 0

# Preferred education level (one of: high_school, bachelor, master, phd)
min_education: bachelor

# Degrees that qualify (matched as substrings)
qualifying_degrees:
  - bachelor
  - b.s.
  - b.tech
  - b.e.
  - master
  - m.s.
  - m.tech
  - m.e.
  - phd
  - ph.d.
  - doctor

# Role/job title keywords that add bonus points
preferred_roles:
  - data scientist
  - ml engineer
  - machine learning engineer
  - ai engineer
  - research scientist
  - data engineer
  - software engineer
  - senior

# Scoring weights (must sum to 100)
scoring_weights:
  skills_match: 50       # How many required skills are present
  experience: 25         # Years of relevant experience
  education: 15          # Education level match
  role_relevance: 10     # Role/title fit

# Output columns (in order)
output_columns:
  - File Name
  - Candidate Name
  - Email
  - Phone
  - Skills Found
  - Skills Score
  - Years Experience
  - Experience Score
  - Education
  - Education Score
  - Current Role
  - Role Score
  - Overall Score
  - Notes