Extracting Keywords from Job Descriptions Like a Pro

Job description keyword matching is the most direct way to increase your ATS score. But copy-pasting keywords is obvious and ineffective. Here's the right approach.

Step 1: Categorise the Keywords

Read the job description and separate keywords into three buckets: hard skills (Python, React, SQL), soft skills (cross-functional collaboration, stakeholder management), and domain terms (CAC, MRR, GTM strategy). Each category requires a different placement strategy.

Step 2: Find the Frequency

Keywords that appear multiple times in a JD are non-negotiable. If "data pipelines" appears four times, it must appear in your resume at least twice — once in skills, once in a bullet.

Step 3: Match Phrasing Exactly

ATS parsers are literal. "Machine Learning" and "ML" may not match. "Project Management" and "project manager" may not match. Mirror the exact phrasing used in the job description.

Step 4: Embed Naturally

Don't keyword-stuff your skills section. Place the most important keywords in your professional summary, then reinforce them in your bullet points with context. "Led ML pipeline migration" is more powerful than just "Machine Learning" in a list.

Step 5: Check Your Match Score

Use CVAgent's JD match tool to see exactly which keywords you're missing and how your current match score compares to the threshold for shortlisting.