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Qu'est-ce que Job Matching ?

Process — manual or algorithmic — of identifying the best correspondence between a candidate's profile and available job opportunities based on skills, experience and preferences.

Definition

Job matching is the process of identifying and evaluating the correspondence between a candidate's profile (skills, experience, location, salary expectations, work preferences) and the requirements of available job opportunities. It can be performed manually by a recruiter, algorithmically by a recommendation engine, or through a combination of both.

In practice

Effective job matching requires precise, structured data on both sides: candidates need well-defined profiles with standardised skill and occupation taxonomies; job offers need consistent requirement specifications. BarnAI uses a multi-factor matching model combining NACE sector alignment (50% weight), geographic proximity (30%), and language competency (20%) to score candidate-job fit. Beyond basic keyword matching (title and skills overlap), advanced matching considers semantic similarity ("Python developer" matches "software engineer with Python experience"), career trajectory fit, and preference alignment. The quality of matching is assessed by acceptance rates, interview-to-offer conversion, and ultimately early tenure performance of matched hires. Machine learning models improve over time as outcome data (interview invites, hires, tenure) provides feedback signals.

Key takeaway

Great job matching reduces wasted time for both candidates and recruiters — the goal is not maximum application volume but maximum relevant connections between the right people and the right opportunities.

Job Matching: definition | BarnAI | BarnAI