ATS Keywords List: How Resume Scanners Read Your Resume
A resume scanner (ATS) extracts the text layer of your resume and runs a keyword search against it. Whether your resume makes the cut depends on how your wording matches the recruiter's search input. This page gives you 200+ ready-to-use ATS keywords by industry and explains how resume scanning actually works.
- What are ATS keywords?
- Top 10 universal ATS keywords (2026)
- ATS keywords by industry: 6 lists
- Hard skills vs soft skills: what ATS prioritizes
- Action verbs ATS scanners recognize
- Do ATS scanners use synonyms or exact matches?
- Can ATS read PDFs, tables, and hidden text?
- How to extract keywords from a job description
- How to format an ATS-friendly resume
- Where to place keywords (without stuffing)
- FAQ
What are ATS keywords?
ATS keywords are the specific words a recruiter types into the applicant tracking system when searching candidates in its database. Your resume passes or fails based on whether the text contains those exact words. ATS search is a database lookup, not a reading comprehension test.
Three things qualify as ATS keywords:
- Hard skills. Tools, software, certifications, methodologies ("Python," "Salesforce," "Six Sigma," "PMP").
- Job titles and levels. Exact role names ("Senior Product Manager," "Lead Data Engineer").
- Industry terminology. Phrases recruiters in that vertical use ("HEDIS reporting" in healthcare, "AR aging" in finance).
Soft skills appear in ATS searches less often. Most recruiters filter by hard skills first and read soft skills later in the shortlist phase.
Top 10 universal ATS keywords (2026)
These 10 phrases appear across nearly every white-collar job posting. Adapt them with your own metrics and use the exact form below if the job description includes them.
Two notes on these. First, "Cross-functional collaboration" is the most common phrase used in postings yet the one candidates most often paraphrase as "worked with other teams." That paraphrase will not match. Second, "ROI" needs to be spelled out at least once because some older Taleo deployments do not index acronyms separately.
ATS keywords by industry: 6 lists
Each block below is a working starting point, not an exhaustive list. These are the keywords for resume scanners that recruiters in each vertical actually search for. Combine 8–12 from your target industry with 3–4 universal terms above, then verify each against the specific job description you are applying to.
Technology & Engineering
Finance & Accounting
Marketing & Sales
Healthcare
Human Resources
Customer Service & Operations
Hard skills vs soft skills: what ATS prioritizes
Recruiters configure ATS searches around hard skills almost always. A search for "Senior Backend Engineer" with required filters of "Python" and "AWS" returns a list. From that list, soft skills get evaluated by humans during shortlist review.
| Skill type | Examples | How ATS uses them |
|---|---|---|
| Hard skills | Python, SQL, Salesforce, GAAP, ICD-10, CPA | Primary filter. Recruiter searches by these and ranks results. |
| Soft skills | Communication, leadership, adaptability | Rarely in the search query. Read on the shortlist, often weighted lower than measurable outcomes. |
| Certifications | PMP, AWS Certified, SHRM-CP | Indexed as hard skills. Spell out acronyms at least once. |
| Job titles | Senior Product Manager, Lead RN | Highest weight when match is exact in your most recent role. |
Put your hard skills in a dedicated Skills section and embed the strongest two or three again inside your role bullets with measurable context. Soft skills belong inside the bullets too, attached to a concrete outcome rather than listed bare.
Action verbs ATS scanners recognize
Action verbs do not improve your ATS score by themselves because most scanners do not weight verbs separately. They matter for human readers who scan your bullets in 6–8 seconds during shortlist review. Strong verbs front-load the bullet and signal scope.
Avoid two patterns: "Responsible for…" (passive, no scope) and "Helped with…" (no ownership). Both pass ATS but fail the human reader.
Do ATS scanners use synonyms or exact matches?
Exact match is the default mode on almost every platform. Assume the scanner reads plain text only, then use find-and-replace to mirror the exact vocabulary in the job description.
Synonym handling differs by platform, and you usually cannot tell which platform an employer uses:
| Platform | Does it recognize synonyms? |
|---|---|
| Taleo | No. "P&L ownership" does not equal "profit and loss." Used by most large enterprises and financial institutions. |
| Greenhouse / Lever | Yes, a basic set of common equivalents. "Python developer" matches "Python engineer." Still depends on employer configuration. |
| Workday | Inconsistent. Behavior depends on each employer's setting. Same ATS, different behavior across companies. |
| Ashby | Similar to Workday but more reliable. Mostly used in tech companies. Scope of synonyms is limited, for example "managed team" is close to "built team." |
Keyword synonyms and semantic inference are two distinct features. The first is a simple lookup table; very few platforms support it. Semantic inference would mean a deep analysis of your experience to understand whether you "built a team of 12 from scratch" (leadership), "drove ARR growth" (financial metrics), or anything else. No ATS uses semantic inference yet because that capability requires a large language model.
Implied competencies do not pass through either. If the job description requires "cross-functional stakeholder management" but your resume mentions "collaboration with various departments," your resume will fail the filter. Use the exact phrase. For more on how newer AI-based screening differs from classic ATS, see how to get past AI resume screening.
Can ATS read PDFs, tables, and hidden text?
ATS processes the text layer of your file only, not the visual rendering.
Modern ATS supports both PDF and DOCX. DOCX is typically easier to process because it does not require additional parsing steps. When in doubt, submit DOCX.
Text in the same color as the background is invisible to people but fully readable by machines. In 2015–2019 some systems processed resumes via image-to-text conversion, but that technique is ineffective now. Greenhouse, Lever, Workday, and Ashby process the text layer directly; Taleo behaves differently depending on deployment year. Hidden white-text keyword stuffing also tends to trigger AI-based fraud detection. See why an AI-written resume passes ATS but gets rejected by recruiters.
When the scanner detects a discrepancy, one of the following happens:
- Keywords are indexed but flagged for manual review
- The system routes your resume for human verification
- Your application may be disqualified automatically
Parsed tables produce a mix of columns and headers detached from row data. They tend to corrupt your resume's structure. Do not use tables in the header, summary, or skills sections. If you need to list items horizontally, use two plain-text columns instead.
How to extract keywords from a job description
A working keyword list comes from the job description itself, not from any generic guide (including this one). Target a 60–80% match against the required skills section. For a posting with 10 required skills, your resume should include 6–8 of them with exact phrasing.
- Paste the full posting into a plain-text doc. Strip the company boilerplate; keep "Responsibilities," "Requirements," and "Qualifications" sections.
- Highlight every noun phrase that repeats twice or more. Repeats are the recruiter's priorities. Those are the search queries they will actually run.
- Pull all named tools, certifications, and methodologies. Each one is a likely filter. Confirm exact spelling and capitalization ("ICD-10" not "icd 10").
- Pull 3–4 postings for the same role from other companies. Phrases that appear in all four are industry-standard and worth keeping even if your target posting omits them.
Doing this manually takes 20–30 minutes per application. Worth it the first three times to internalize the pattern. After that, automate the extraction. See which parts of job search to automate with AI.
How to format an ATS-friendly resume
ATS expects a specific structure. Five rules cover the common failures:
- Single-column layout. Multi-column designs split text into fragments that merge incorrectly during parsing.
- Standard section headings: Experience, Education, Skills. Creative labels like "Where I Have Been" or "What I Have Done" are not recognized.
- Contact info in the main body, not in headers or footers. Most parsers ignore those areas.
- No text boxes or images. Text inside them is unreadable to the parser.
- No tables in sections. Use plain bullets instead.
Vocabulary matching is what ATS needs. The harder problem is sentence structure. A recruiter opens your resume and finds sentences copied verbatim from the posting, with no result attached. That fails the human review even if the keywords passed the filter.
Same keywords as the posting, plus details and context. The ATS still matches them. The recruiter sees a result.
Where to place keywords (without stuffing)
A high percentage of keywords relative to visible text triggers manual review instead of automatic approval. ATS weights keywords by their placement, not by raw frequency.
| Placement | Weight |
|---|---|
| Job title | Maximum. Use the exact job title from the posting. |
| Summary | High. Up to 3–4 priority keywords in 2–3 opening sentences. |
| First bullet of each role | Medium. Each position starts with a keyword tied to a measurable achievement. |
| Skills section | Low. Tools and technologies, not soft skills. |
One keyword in your job title works better than the same keyword in 6 bullet points.
Extract 8–10 priority phrases from the job description. Write a separate bullet for each, linking the phrase to a specific outcome. Put top priorities in the title and summary; distribute the rest across role bullets with concrete numbers.
