Your Resume May Be Getting Misread Before a Recruiter Sees It

A rejection email can make you think one thing: I wasn't qualified enough. But sometimes the problem happens earlier than that. Before a recruiter decides whether your experience fits a role, the hiring system may first need to extract information from your resume — your job titles, employers, dates, skills, education, and other details. That process is called resume parsing, and if the document is hard for the software to interpret, the information stored in your candidate profile may not accurately reflect what you actually submitted.

That doesn't mean an ATS automatically rejected you. In many systems, a parsing problem just means the information has to be corrected or reviewed manually. But it creates an unnecessary obstacle between your resume and the person evaluating it.

The ATS doesn't see your resume the way you do. You see a polished two-column resume. A parsing system sees a document that needs to be converted into structured data, and that distinction matters more than most job seekers realize. Greenhouse's own support documentation lists several formatting issues that can cause an unsuccessful or partial resume parse — graphics, photos, tables, headers and footers, text boxes, and columned layouts among them. Workday describes something similar: its parsing runs on natural-language processing that looks for patterns, and Workday's own site notes that a good system should recognize "managed team of five" and "led five-person team" as conveying similar information. In other words, a resume can look perfectly organized to a human and still get interpreted incorrectly by the software standing between you and that human.

The biggest formatting risks:

Two-column layouts. A human reader instantly understands that the left side holds your skills and the right side holds your work experience. A parser has to infer that relationship from the document's structure instead, and it doesn't always get there — a simple, single-column layout remains the safer choice for most conventional applications.

Tables. They're useful for designing a document, but they introduce risk when job titles, dates, or skills sit inside table cells rather than as plain text. If your work history lives in a table, pull the extracted text out and check whether it still makes sense before you submit it.

Headers and footers. Your name and contact information might look perfectly visible at the top of the page, but plenty of parsers handle headers, footers, and text boxes unreliably. Greenhouse specifically flags contact information placed in a header, footer, or text box as a common cause of parsing problems — keep that information in the main body of the document instead.

Images and graphics. A logo or decorative graphic isn't a problem for a human reader, but text embedded inside an image is a different story. If your phone number, job title, or skills are baked into an image, the system likely won't extract them as text — and the same goes for scanned resumes, which are really just photographs of a document rather than readable text.

A test that takes about 30 seconds: open your finished resume, select all the text, and paste it into a plain-text app like Notepad with formatting stripped out. Then read what you pasted — is your employment history still in the right order, with each job title attached to the correct company and dates, and are your skills and contact details still there? If anything disappears or lands in a strange order, don't assume the system will interpret your original design the way you intended. Fix the document first.

But formatting isn't the only issue. A perfectly readable resume can still be a poor match for a particular job. Modern recruiting platforms aren't all built the same way — some use parsing mainly to turn documents into structured candidate profiles, while others layer on search, matching, ranking, or AI-assisted screening. There isn't one universal "ATS algorithm," which is also where a lot of online resume advice gets misleading.

You don't need to stuff your resume with every keyword from a job description. You do need to describe your actual experience in language that clearly connects to the role. If a posting asks for "customer relationship management and Salesforce experience" and your resume says you "managed enterprise accounts and maintained customer records in Salesforce," you've done more than insert keywords — you've connected the terminology to real experience. That's the goal.

Use the job description as a vocabulary guide. Look for job titles, technical skills, software and tools, certifications, industry terminology, functional responsibilities, and anything explicitly listed as required. If the employer calls a skill "Search Engine Optimization (SEO)," don't rely only on an unrelated synonym — if you genuinely have that experience, use the employer's own terminology somewhere in your resume so the connection is unmistakable. Just don't add skills you don't have simply because they appear in the posting; keyword stuffing makes a resume harder for a human recruiter to read, and the human is still the one who decides whether you get the interview.

The bigger mistake is optimizing for the machine instead of the recruiter. A lot of ATS advice online claims systems reject resumes over an exact keyword percentage or one synonym instead of another. The reality is more complicated — Workday, for instance, says its natural-language processing can recognize that different phrasings describe the same underlying experience, which means modern recruiting technology can do more than simple word counting. That doesn't mean keywords don't matter. It means context matters too. Your goal isn't to trick an ATS — it's to make your qualifications easy for both software and humans to understand.

A pre-submission checklist:

Format: Use a simple, single-column layout for most applications. Avoid putting important information inside tables, text boxes, or graphics. Keep your contact information in the main document body. Make sure your PDF contains selectable text, not a scanned image.

Structure: Use conventional section headings — Experience, Education, Skills. Keep job titles, company names, and dates clearly attached to each position. Stay consistent with formatting throughout.

Content: Identify the requirements that matter most in the job description. Make sure your resume clearly shows which of them you meet. Use the employer's own terminology where it accurately describes your experience. Quantify your achievements where you can. Don't add keywords or skills you can't defend in an interview.

Final test: Copy and paste the whole resume into a plain-text document, check that the information still reads in the right order, and open the final file yourself before you submit it.

Your resume doesn't need to beat an algorithm. It needs to survive the technology without becoming worse for the human reading it — that's the balance most candidates miss. Use simple formatting so the system can extract your information, use relevant terminology so your experience is easy to match to the role, then write the actual content for the person who will eventually decide whether you get an interview. An ATS-friendly resume isn't one that looks like it was written for a machine. It's one that makes your qualifications easy for both machines and people to understand.