Every job description is a keyword list with extra steps. Behind the narrative language about 'dynamic environments' and 'collaborative cultures' are specific, scorable terms that the ATS uses to rank candidates. Knowing how to extract those terms systematically is one of the most valuable job-search skills you can develop. Once you can reliably decode a job description, you can tailor any resume to any role with speed and confidence.
Try It FreeCopy and paste it into a plain text document or a notes app. Working in a separate document also lets you add notes and highlights without losing your place. Title the document with the company name, role title, and date, so you can refer back to it later.
Some also include a section on the team or company. Read through the posting and mark where each section begins. This matters because keywords in the required qualifications section are non-negotiable for ATS scoring, while keywords in the preferred section are bonus points. Prioritize your required terms first.
Highlight every specific tool, technology, certification, programming language, platform, methodology, or system mentioned. Write each one down exactly as it appears: 'Tableau' not 'data visualization tool,' 'AWS EC2' not 'cloud computing.' Then go through the responsibilities section and add any tools or technologies mentioned there. Finally, check the preferred qualifications section and add those terms to a separate 'bonus keywords' list. You now have a prioritized hard skills checklist.
These matter for ATS scoring because they appear in the job description and will be scored as keyword matches if they appear in your resume. List them separately from your hard skills.
A term that appears three or four times is almost certainly a core requirement that the recruiter will specifically look for. Go back through your keyword lists and put a number next to each term indicating how many times it appears in the full job description. Sort your list by frequency. These high-frequency terms should appear in your professional summary and in your most prominent experience bullets - not just in the skills section at the bottom.
If the title is 'Senior Data Analyst,' your resume should use that exact phrase or a very close equivalent in your summary or most recent job title. Also read the company description or 'about us' section for any industry-specific terminology that might appear in what the ATS is configured to match. If the company is in fintech, terms like 'financial data,' 'regulatory compliance,' or 'risk management' might be additional scoring opportunities even if they appear only once.
Check your resume against any job description in under 60 seconds.
Add to Chrome for FreeA typical job description yields 15-25 meaningful keywords after you remove generic phrases and duplicates. From that list, 8-12 are usually high priority (appear in required qualifications or more than once), and the rest are secondary. You do not need to include every keyword on your list - focus on the ones you have genuine experience with. A resume that addresses all 10 high-priority terms accurately will score better than one that tries to address all 25 with weak or forced mentions.
Yes, but they need to appear in context to score well. Simply listing 'strong communicator' in a skills section is not enough. Write a bullet point that demonstrates the behavior: 'Presented quarterly business reviews to C-suite stakeholders across three business units' demonstrates communication and stakeholder management skills more powerfully than claiming them. The ATS scores the keyword; the recruiter evaluates whether you have demonstrated the skill.
This is normal and expected. Different companies use different terminology for the same concepts - one company says 'sprint planning' and another says 'Agile ceremonies.' When you see variation, use the terminology from the specific job description you are applying to. If you are applying to both companies, create two tailored versions of your resume. Never send the same resume to two roles that use meaningfully different keyword sets and expect strong scores from both.
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