Intelligent resume parsing and candidate screening with bias-reduction capabilities
The Resume Parsing and Screening skill provides intelligent resume analysis and candidate evaluation capabilities. This skill enables structured data extraction, skills matching, fit scoring, and bias-reduction through standardized evaluation methods.
const parseConfig = {
format: 'auto-detect',
extractFields: [
'contact',
'experience',
'education',
'skills',
'certifications'
],
normalization: {
titles: true,
companies: true,
skills: 'standard-taxonomy'
},
redFlagRules: {
maxGapMonths: 12,
minTenureMonths: 12,
flagJobHopping: true
}
};
const scoringCriteria = {
jobRequirements: {
requiredSkills: ['Python', 'SQL', 'Machine Learning'],
preferredSkills: ['AWS', 'Spark', 'Docker'],
minExperienceYears: 5,
education: {
required: 'Bachelors',
preferredFields: ['Computer Science', 'Data Science']
}
},
weights: {
requiredSkills: 40,
preferredSkills: 20,
experience: 25,
education: 15
},
thresholds: {
autoAdvance: 80,
review: 60,
autoReject: 40
}
};
This skill integrates with the following HR processes:
| Process | Integration Points |
|---|---|
| full-cycle-recruiting.js | Candidate screening, ranking |
| structured-interview-design.js | Interview focus areas |
| Metric | Description | Target |
|---|---|---|
| Screening Accuracy | Correlation with interview performance | >0.7 |
| Time to Screen | Minutes per resume | <5 min |
| Adverse Impact | Score distribution across groups | No significant difference |
| False Positive Rate | Low-fit candidates advanced | <15% |
| False Negative Rate | High-fit candidates rejected | <10% |