What Does Greenhouse ATS Look for in a Resume?

Greenhouse is one of the most widely used ATS platforms in the tech industry, powering hiring at thousands of companies from Series A startups to Fortune 500 firms. Unlike older enterprise systems like Taleo, Greenhouse is a modern recruiter-workflow tool — it parses resumes cleanly and presents candidate profiles to hiring managers in a structured card view. Understanding how it works gives you a concrete optimisation target.

How Greenhouse Parses Your Resume

• Greenhouse uses its own parser to extract: name, contact info, work experience (company, title, dates, description), education, and skills
• It supports .PDF, .DOCX, .DOC, .RTF, and .TXT — PDF is well-supported since Greenhouse's parser is more modern than legacy systems
• It does NOT extract content from tables, text boxes, multi-column sections, or graphics — these regions are silently skipped
• LinkedIn URL in your resume is recognised and linked to your profile in the recruiter's view
• Missing sections (no skills listed, no dates on experience) are flagged for recruiters as incomplete profiles

What Greenhouse Scoring Actually Looks Like

Greenhouse itself does not calculate an ATS match score the way dedicated scoring tools do. Instead, recruiters in Greenhouse use keyword search and filters to find candidates. This means your resume needs to contain the exact search terms a recruiter would type — job title, core skills, tools, and technologies — because they are actively filtering candidate pools by those exact words. If your profile doesn't surface in those searches, you don't exist in their pipeline.

Optimising for Greenhouse: Practical Rules

• Use the exact job title from the posting in your summary — Greenhouse recruiter search starts with title
• List all tools and technologies by full name in a dedicated skills section — recruiters search for "Figma", "PostgreSQL", "Terraform" etc.
• Date all experience entries — Greenhouse displays "no dates found" as a red flag in candidate profiles
• Keep formatting clean and single-column — Greenhouse renders the parsed text in a structured card; complex layouts break the flow
• Include your LinkedIn URL — most Greenhouse workflows cross-reference profiles
• Avoid all-caps section headers — some Greenhouse parser versions handle mixed-case better than ALLCAPS for section detection

Greenhouse vs Workday vs Lever

Greenhouse and Lever are both modern, recruiter-centric ATS platforms popular with tech companies. Workday is more common in large enterprises and has a stricter parser. Taleo (Oracle) is the oldest and most keyword-rigid. The practical implication: Greenhouse and Lever are more forgiving of minor formatting variations, but keyword coverage still determines whether you surface in recruiter searches.