Job descriptions vary widely in their level of detail. Some are generic, aiming to attract a broad range of applicants, while others are so detailed that few may qualify, and even fewer may possess all the listed requirements.
Resumes are not always customized for specific job applications. When they are, they often include numerous skills and buzzwords to navigate applicant tracking systems (ATS) or similar systems.
Driven by Artificial Intelligence (AI), Talent Opinion leverages a combination of an in-house knowledge base, NLP Models, and Large Language Models (LLMs) to analyze job descriptions (role requirements) and resumes. This deep analysis determines their compatibility.
The result is a human-like analysis that reads as if provided by a colleague, contrasting with traditional matching algorithms or some Machine Learning (ML) Models that rely on rigid pattern recognition and generate table-like results.
Talent Opinion considers the broad spectrum of job requirements and the candidate's resume, identifying skills that directly match through the analysis.
Furthermore, the comprehensive analysis enables the AI to infer experience, skills, and job history from the resume and job description. It recognizes potential matches in unspecified details and suggests transferable skills and knowledge from the candidate's past experiences, akin to insights provided by a colleague.
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