Scoring In Candidate Skill Ranking – RChilli HelpDesk

RChilli's Candidate Skill Ranking within the Search & Match API uses a sophisticated scoring mechanism to evaluate how well a candidate's resume matches a job description or search query. The scoring system is dynamic and customizable, empowering recruiters and platforms to tailor results based on their unique needs.

How the Scoring Mechanism Works

RChilli’s scoring logic functions in two layers:

1. Default (Baseline) Logic

Uses predefined weights for attributes such as:
- Skills
- Education
- Location
- Domain
- Tools, Languages, etc.
Designed for quick, out-of-the-box use.
Ideal for new users or systems with no custom tuning needs.

2. Configurable (Customizable) Logic

Users can manually assign weightage to different attributes using the front end.
Examples of customization:
- Emphasize education more heavily (e.g., 30%) if academic background is critical.
- Prioritize location proximity if local candidates are preferred.
These custom weights dynamically influence the match score returned by the API, while the backend logic remains consistent.

Factors Used in Scoring

The match score is derived from multiple fields, depending on availability and relevance:

Skills Match – direct and taxonomy-enriched skills.
Experience – years/months in relevant roles.
Education – level, institution, relevance.
Job Title – exact or approximate matches based on taxonomy.
Domain Expertise – domain alignment of job and candidate.
Location Proximity – city/state/country relevance.

You can use facets and filters to fine-tune the search further (e.g., filter by years of experience).

Score Customization Tools

To implement and manage scoring configurations:

Access the scoring control through RChilli MyAccount.
Adjust weightings as per business priorities.
Refer to this help article for setup: How scoring is calculated.

Maintenance of the Scoring Mechanism

Taxonomy & Scoring Logic are refreshed monthly.
Ensures up-to-date alignment with:
- Industry changes
- New job roles and skills
- Multilingual terms
- Government-compliant standards.

Summary

Component	Description
Default Logic	Predefined, out-of-the-box scoring weights
Custom Logic	User-defined scoring emphasis for tailored search & match
Taxonomy Integration	Enhances skill/job relevance using synonyms and structured classification
Real-Time Impact	Front-end changes reflect immediately in API results

Useful Links

If you need help fine-tuning your scoring setup or running performance comparisons, reach out to support@rchilli.com