Our Proprietary Matching Engine

At the heart of plshireme.ca is our proprietary AI matching engine. Unlike traditional Applicant Tracking Systems (ATS) that rely on simple keyword scanning, our engine is built to understand the context, impact, and nuance of your professional history, much like an expert hiring manager would.

A Multi-Factor Analysis

Our scoring model evaluates your candidacy based on several weighted factors:

1. Requirement Deconstruction: The engine first dissects a job description into atomic requirements and classifies each one into a category: hard_skill, experience, education, certification, soft_skill, or job_duties. It also determines if a requirement is mandatory, preferred, or nice_to_have.

2. Strength of Evidence: Our model doesn’t just see a skill; it evaluates how strongly your resume supports it.

   • Strong Evidence: A resume line with a specific, quantifiable achievement (e.g., “Increased revenue by 30% using Python scripts”).
   • Moderate Evidence: A description of a relevant responsibility (e.g., “Developed REST APIs with FastAPI”).
   • Weak Evidence: A simple keyword mention (e.g., a “Skills” section listing “Python”). These evidence levels are converted into a weighted fulfillment score.

3. Role-Based Weighting: The algorithm understands that different roles have different priorities. For a technical role, hard_skill scores are heavily weighted, while for a sales role, experience and soft_skill scores are more critical.

4. Relevancy Score (Intent Score): Beyond matching requirements, we calculate a Relevancy Score. This uses semantic analysis to measure the cosine similarity between your agent’s search query (e.g., “Senior Backend Engineer”) and the job title itself. This helps filter out jobs with misleading titles.

5. Penalties and Bonuses:

   • Mandatory Penalty: A penalty is applied for each mandatory requirement that is not fulfilled.
   • Knock-Out Penalty: If you don’t meet any of the core mandatory requirements (like essential hard skills or years of experience), your score is drastically reduced, as this is often a deal-breaker for recruiters.
   • Experience Level Penalty: If our AI determines you are significantly underqualified or overqualified for the role’s seniority level, a penalty multiplier is applied to the final score.
   • Nice-to-Have Bonus: Fulfilling “nice-to-have” requirements adds a small bonus to your score.

The Final Match Score

The result of this comprehensive analysis is your Match Score. This is a single, reliable metric representing the strength of your candidacy, allowing you to instantly see which jobs are worth your time.