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Resume Skills Section: What to Include with Examples

By Joshua Giles16 January 20269 min read

The Skills Section: Small Space, Big Impact

The skills section of your resume helps recruiters quickly assess if you're qualified. Done right, it gets you past ATS systems and into interviews.

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Types of Skills to Include

Hard Skills

Specific, teachable abilities that can be measured:
  • Programming languages (Python, JavaScript, SQL)
  • Software proficiency (Excel, Salesforce, Figma)
  • Technical certifications (AWS, PMP, CPA)
  • Language fluency (Spanish - Professional, Mandarin - Native)
  • Industry tools (JIRA, Tableau, AutoCAD)

Soft Skills

Interpersonal abilities that describe how you work:
  • Leadership
  • Communication
  • Problem-solving
  • Collaboration
  • Time management
Note: Soft skills are better demonstrated in your experience bullets than listed in the skills section.

Technical Skills

Industry-specific technical knowledge:
  • Financial modeling (Finance)
  • A/B testing (Marketing)
  • Statistical analysis (Data Science)
  • User research (UX Design)
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Skills Section Formats

Simple List Format

Best for ATS and quick scanning:

Skills: Python, SQL, Tableau, Excel, Statistical Analysis, A/B Testing, Google Analytics, Machine Learning

Categorized Format

Best for diverse skill sets:

Technical: Python, R, SQL, Spark, Hadoop Visualization: Tableau, Power BI, D3.js Cloud: AWS (S3, EC2, Lambda), GCP (BigQuery) Certifications: AWS Data Analytics Specialty, Google Data Engineer

Proficiency Level Format

Use sparingly - can backfire:

Programming:

  • Python (Expert)
  • JavaScript (Proficient)
  • Go (Familiar)
Warning: Only use this if you can back it up. "Expert" invites expert questions.

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Skills by Industry

Software Engineering


Languages: Python, JavaScript/TypeScript, Java, Go
Frontend: React, Vue, HTML/CSS, Redux
Backend: Node.js, FastAPI, PostgreSQL, MongoDB
DevOps: Docker, Kubernetes, AWS, CI/CD
Tools: Git, JIRA, Figma, DataDog

Data Science / Analytics


Languages: Python, R, SQL
ML/AI: TensorFlow, PyTorch, Scikit-learn
Analytics: Pandas, NumPy, Spark
Visualization: Tableau, Power BI, Matplotlib
Cloud: AWS Sagemaker, GCP BigQuery, Snowflake

Product Management


Product: Roadmapping, PRDs, User Stories, A/B Testing
Analytics: SQL, Amplitude, Mixpanel, Google Analytics
Tools: JIRA, Productboard, Figma, Miro
Methodologies: Agile, Scrum, Design Thinking

UX/UI Design


Design: Figma, Sketch, Adobe XD, Illustrator
Research: User Interviews, Usability Testing, Surveys
Prototyping: InVision, Principle, Framer
Skills: Design Systems, Accessibility (WCAG), Mobile Design

Marketing


Digital: Google Ads, Meta Ads, SEO, SEM
Analytics: Google Analytics, HubSpot, Marketo
Content: CMS, Mailchimp, Hootsuite, Canva
Skills: A/B Testing, CRO, Marketing Automation

Finance


Technical: Financial Modeling, Valuation, DCF Analysis
Tools: Excel (Advanced), Bloomberg Terminal, Capital IQ
Software: SAP, Oracle, Quickbooks
Certifications: CPA, CFA Level II, Series 7 & 63

Project Management


Methodologies: Agile, Scrum, Waterfall, Kanban
Tools: JIRA, Asana, MS Project, Monday.com
Certifications: PMP, PRINCE2, CSM
Skills: Stakeholder Management, Risk Assessment, Budgeting

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What NOT to Include

Outdated Skills

  • Microsoft Office (assumed for most roles)
  • Basic computer skills
  • Typing speed
  • Fax machines

Vague Skills

  • "People person"
  • "Hard worker"
  • "Quick learner"
  • "Detail-oriented" (show, don't tell)

Irrelevant Skills

  • Skills unrelated to target role
  • Personal hobbies (unless relevant)
  • High school achievements

Inflated Skills

  • Don't list languages you haven't used in years
  • Don't claim "expert" level lightly
  • Don't include skills you can't discuss in an interview
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Keyword Optimization for ATS

Match the Job Description

If the job posting says: "Proficiency in Python and SQL required. Experience with AWS and Kubernetes preferred."

Your skills should include:

  • Python
  • SQL
  • AWS
  • Kubernetes

Use Both Formats

  • "JavaScript" and "JS"
  • "Project Management Professional" and "PMP"
  • "Customer Relationship Management" and "CRM"

Mirror Exact Terminology

Job says "Salesforce" → Use "Salesforce" (not "SFDC") Job says "Adobe Creative Suite" → Use that exact phrase

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Skills Section Placement

Top of Resume (Skills-First)

Best for:
  • Career changers
  • Roles with specific technical requirements
  • ATS optimization

After Experience

Best for:
  • Traditional formats
  • When experience is your strongest asset
  • Senior roles
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Examples by Career Stage

Entry Level / Graduate


Skills: Python, SQL, Excel, Google Analytics, HTML/CSS
Coursework: Statistics, Machine Learning, Database Design
Certifications: Google Analytics Certified

Mid-Level Professional


Technical: Python, SQL, Tableau, AWS (EC2, S3, Lambda)
Analytics: A/B Testing, Statistical Modeling, Cohort Analysis
Tools: JIRA, Confluence, Git, dbt

Senior Professional


Leadership: Team Management (8 direct reports), Strategic Planning
Technical: Python, SQL, Spark, ML Pipelines
Architecture: Data Warehouse Design, ETL Optimization
Cloud: AWS Solutions Architect (Professional Certified)

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Final Tips

  • Tailor for each application - Different roles need different skills highlighted
  • Quantify where possible - "Excel" vs "Excel (VLOOKUPs, Pivot Tables, Macros)"
  • Be honest - You will be asked about anything you list
  • Update regularly - Add new skills, remove outdated ones
  • Use the job description - It tells you exactly what they want
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    Related Resources

  • US Salary Guide - See what skills command the highest salaries
  • resume skillsskills sectiontechnical skillshard skillssoft skills
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