Extract and analyze resume keywords

To extract and analyze resume keywords, here’s a complete process you can follow, including which keywords to look for, how to extract them, and how to analyze their relevance based on a job description.

---

1. What Are Resume Keywords?

Resume keywords are specific terms and phrases that employers use in job descriptions. They typically fall into these categories:

• Job titles

• Skills (technical and soft)

• Certifications

• Tools and technologies

• Education or degrees

• Industry-specific terms

---

2. How to Extract Keywords from a Resume

Manual Extraction

Look for:

• Skills section: Hard and soft skills.

• Experience bullets: Action verbs + tools/methods used.

• Certifications and education: Degree names, certification titles.

• Job titles: Reflects roles, e.g., “Digital Marketing Specialist.”

Automated Extraction (Using Tools or Scripts)

If using a script (e.g., Python), you can parse the resume and extract frequent nouns and verbs. Libraries such as spaCy, nltk, or even TF-IDF in sklearn can help.

Example Output:

• Hard Skills: Python, Excel, SQL, Tableau

• Soft Skills: Communication, Teamwork, Leadership

• Certifications: PMP, AWS Certified Solutions Architect

• Tools: Salesforce, HubSpot, Jira

---

3. Extracting Keywords from a Job Description

Take the job description and identify:

• Must-have skills

• Preferred qualifications

• Tools and platforms mentioned

• Role-specific language

Example:

Job Title: Data Analyst
Job Description Excerpts:

• “Experience with SQL, Python, and Tableau”

• “Ability to conduct data visualization”

• “Excellent analytical and communication skills”

• “Bachelor’s degree in a quantitative field”

Keywords:

• SQL, Python, Tableau

• Data visualization

• Analytical skills

• Communication skills

• Bachelor’s degree

• Quantitative field

---

4. Resume vs. Job Description Keyword Match Analysis

Comparison Strategy:

• Create two keyword lists (Resume vs Job Description)

• Match terms in each category

• Highlight gaps or strengths

Example Match Table:

---

5. Optimization Strategy

• Add missing job description keywords if they apply to your experience.

• Use exact wording as in the job description for Applicant Tracking Systems (ATS).

• Avoid keyword stuffing. Keep the resume natural and readable.

• Tailor each resume to the job description—there’s no one-size-fits-all.

---

6. Useful Keywords by Industry

Software Development

• Java, React, Git, REST API, Agile, CI/CD, Docker, Kubernetes

Digital Marketing

• SEO, SEM, Google Analytics, Facebook Ads, A/B Testing, CRM, Content Strategy

Finance

• Financial Modeling, Excel, SAP, GAAP, Forecasting, Risk Analysis

Healthcare

• Patient Care, HIPAA, EMR, Medical Terminology, Clinical Research

Project Management

• Scrum, Agile, Waterfall, Jira, Stakeholder Management, Risk Mitigation

---

7. Tools for Keyword Analysis

• Jobscan.co: Compares resume to job description.

• Resumeworded.com: Gives keyword insights and optimization tips.

• Zety / Novoresume: Resume builders with keyword suggestions.

• LinkedIn Skills Matcher: Suggests skills for specific roles.

---

8. Final Tips

• Prioritize keywords with the highest frequency in the job description.

• Use action verbs with keywords: “Led Python-based automation” vs “Python”.

• For ATS, place keywords in bullet points, summary, and skills section.

• Customize your resume headline and summary to include top keywords.

---

Let me know if you’d like to analyze a specific resume or job description—I’m happy to run a comparison or extract keyword lists for you.