Understand the exact parsing pipeline and candidate ranking algorithms used by Workday, Taleo, Greenhouse, and Lever before your resume ever reaches human eyes.
Your PDF or DOCX file is fed into the OCR engine. Text layers are stripped of formatting and extracted into a linear stream.
Natural Language Processing (NLP) categorizes data into discrete fields: Contact Info, Work History, Education, and Skills.
The candidate record is evaluated against job criteria. Exact match strings and semantic vector embeddings (SBERT) determine relevance.
Recruiters view a prioritized candidate leaderboard. Only applicants in the top 10–20% match tier receive human review.
Applicant tracking systems are programmed to reject what they cannot read. When candidates submit resumes designed in complex graphic design tools with multi-column tables, text frames, or non-standard fonts, the parser produces jumbled garbage.
Scoring high does not require tricking the ATS. It requires presenting your authentic experience in the exact semantic structure that the ATS indexes for the target role.