Proprietary data

ATS Keyword Effectiveness Index

Most keyword advice is guesswork. This index is measured: every row compares the average ATS match score of resumes that contain a keyword against those that do not.

Across 1,371 resume analyses, 50 keywords appear often enough to measure. The largest measured effects come from process and domain terms, not generic soft skills. Several common soft skills correlate with a lower score, because they crowd out the concrete requirements a job description asks for.

Resume analyses
1,371
Keywords measured
50
Data window
Last 90 days

Last updated:

Keywords that raise the score

Average match score with the keyword present, minus the score without it.

Keyword Score impact Observations Most common roles
microservices +6.8 32 medium confidence Senior Software Engineer, .NET Technical Architect
aws +6.4 68 high confidence Senior Data Engineer, Software Engineer
risk management +4.8 26 medium confidence Senior Financial Manager / Financial Controller, Senior Cybersecurity Architect
team leadership +4.6 44 medium confidence Senior Financial Manager / Financial Controller, Head of Brand and Creative
spring boot +4.4 24 medium confidence Software Engineer, Full Stack Developer
data visualization +4.3 26 medium confidence Data Analyst, Tableau Data Analyst / Business Intelligence Analyst
mentoring +4.2 49 medium confidence Data Governance Manager, Senior Cybersecurity Architect
kubernetes +4.1 33 medium confidence Senior Software Engineer, DevOps Engineer
typescript +3.8 38 medium confidence Senior Software Engineer, Software Engineer
data analysis +3.6 67 high confidence Energy Market Analyst, Tableau Data Analyst / Business Intelligence Analyst
power bi +3.3 73 high confidence Data Analyst, Data Engineer
ci/cd +3.3 32 medium confidence Senior Backend Developer, DevOps Engineer
java +3.2 53 high confidence Software Engineer, Full Stack Developer
cross-functional collaboration +3.1 44 medium confidence Pharmacovigilance Specialist / Drug Safety Associate, Learning & Development Program Manager
documentation +3.0 30 medium confidence IT Support Technician, IT Support Technician (L1/L2)
training +2.8 41 medium confidence Data Governance Manager, Inventory Control Accountant
postgresql +2.7 32 medium confidence Senior Backend Developer, Senior Software Engineer / Cloud Infrastructure Engineer
stakeholder management +2.4 85 high confidence Learning & Development Program Manager, Tableau Data Analyst / Business Intelligence Analyst
c# +2.4 23 medium confidence Full Stack Engineer, Back-End Developer
node.js +2.3 54 high confidence Software Developer, Software Engineer

Keywords that do not help

Present on resumes that score below average. Usually a sign the keyword replaces a specific requirement rather than adding one.

Keyword Score impact Observations Most common roles
git -6.1 35 medium confidence Data Analyst / Marketing Analyst, AEM Full Stack Developer
time management -5.3 40 medium confidence Humanitarian Project Coordinator, Humanitarian Programme Specialist / Project Coordinator
adaptability -5.0 27 medium confidence Humanitarian Project Coordinator, Accountant / Comptable
teamwork -4.8 77 high confidence Humanitarian Project Coordinator, Humanitarian Programme Specialist / Project Coordinator
problem-solving -3.6 27 medium confidence Humanitarian Project Coordinator, Customer Service Representative
communication -3.2 177 high confidence Data Governance Manager, Humanitarian Project Coordinator
attention to detail -2.6 46 medium confidence Pharmacovigilance Specialist / Drug Safety Associate, Humanitarian Programme Specialist / Project Coordinator
customer service -2.2 42 medium confidence Administrative Assistant / Front Office Receptionist, Administrative and Front Office Support Specialist
docker -1.1 50 medium confidence Data Analyst / Marketing Analyst, Senior Backend Developer
problem solving -0.7 108 high confidence Inventory Control Accountant, Data Governance Manager

How this is measured

Every ATS analysis run through ATS CV Checker produces a match score plus the list of job-description keywords that were found in the resume and the ones that were missing.

For each keyword we compute the average score of analyses where it was present and the average where it was missing. The difference is the score impact shown above.

Only keywords with enough observations are published. Aggregates are anonymous: no resume text, employer, or personal data is exposed, and figures are rounded.

What this does not measure

These figures describe our matching model, not hiring outcomes. A higher match score means a resume covers more of what a job description asks for. It is not a prediction that you will get an interview, and no public dataset can honestly claim that.

See these keywords against your own resume

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