How ATS Software Parses a Resume, Step by Step
Short answer: An ATS extracts raw text, splits it into sections by headings, then maps entries to fields like job title and dates. Columns, tables, images, and creative headings are the most common ways this fails.
Step 1: Text extraction
The system pulls raw text from your PDF or DOCX. Text in images or scanned pages cannot be extracted without OCR, and OCR is error-prone.
Step 2: Section detection
Parsers look for known headings such as "Work Experience" and "Education". Nonstandard titles like "Where I've Been" can cause entire sections to be missed.
Step 3: Field mapping
Within each section, the parser identifies employer, title, dates, and bullets. Consistent date formats help; so does placing title and company on predictable lines.
Step 4: Search and filtering
Recruiters search the stored profile by skills, titles, and location. Your job is to make sure the terms they would search appear naturally in your resume.
What commonly breaks parsing
- Multi-column layouts and text boxes
- Tables used for layout
- Contact details inside headers or footers
- Icons and decorative fonts
- Image-only PDFs
FAQ
Can ATS read PDFs?
Yes, if the PDF contains real text. Image-based or scanned PDFs generally cannot be read reliably.
Is DOCX safer than PDF?
Both work when exported cleanly. Follow the instructions on the job posting if it specifies a format.