Seventy percent of employers now use skills-based hiring, up from 65% last year (NACE Job Outlook 2026). That means the skills for a resume are no longer supplementary. They are the first filter. This guide covers what to list, what to skip, how to format the section for ATS, and includes 300+ role-specific resume skills examples backed by the latest hiring data, plus copy-paste skills sections for 11 industries.

The Quick Answer: What Skills to Put on a Resume

List 8 to 12 skills, weighted roughly 60% hard skills and 40% soft skills, and pull the exact wording from the job posting. Hard skills (tools, languages, certifications, measurable proficiencies) carry the ATS keyword match. Soft skills earn their place only when the posting names them and your work experience proves them.

Group them under labelled sub-headings rather than one long comma-separated line. A recruiter scanning for six seconds and a parser scanning for keywords both read grouped skills faster, and grouping is what separates the before/after examples further down this page.

Skip anything that is a baseline expectation (Microsoft Word, email, "hard worker"), anything you could not answer a follow-up question about, and anything the posting never mentions.

Why Your Skills Section Can Make or Break ATS Screening

82.3% of companies use Applicant Tracking Systems to screen resumes before a human reads them (Novoresume survey, 203 HR professionals). ATS filters work primarily by matching keywords in your resume against keywords in the job posting. The skills section is one of the first places those systems look.

At the same time, 70% of employers are now using skills-based hiring during screening (NACE Job Outlook 2026, up from 65% the prior year). This means recruiters are explicitly trained to look for skills evidence, not just job titles and degrees. A skills section that is vague, generic, or mismatched to the role hurts you at both the ATS and human review stages.

ATS Stage

Scans for keyword matches against job description. Skills section is a primary source. Missing keywords means filtered out.

Recruiter Stage (20 sec)

74% of recruiters spend 20 seconds or less skimming a resume (Novoresume). The skills section delivers instant role-fit signal.

Hiring Manager Stage

88% of hiring managers focus on hard skills when reading resumes (Enhancv). Specific tools and technologies outperform generic categories.

Hard Skills vs. Soft Skills: The 60/40 Framework

Hard skills are specific, teachable, and measurable: Python, financial modeling, HIPAA compliance, Adobe Illustrator. Soft skills describe how you work: communication, adaptability, problem-solving. Both matter, but for different reasons and different audiences.

Dimension Hard Skills Soft Skills
DefinitionSpecific, role-related technical abilitiesInterpersonal and behavioral traits
How learnedTraining, courses, degrees, practiceExperience, coaching, reflection
How verifiedCertifications, portfolios, testsReferences, behavioral interviews
ATS impactHigh: primary keyword matchModerate: select terms match
ExamplesSQL, Salesforce, Project Management, GAAPCommunication, Adaptability, Leadership
Shelf lifeCan become outdated (Flash, legacy ERP)Transferable and durable

A December 2025 survey of 1,005 U.S. hiring managers (ResumeTemplates.com) found 62% say hard and soft skills are equally valuable. 24% say soft skills matter more. Only 14% prioritize hard skills alone, and that figure has dropped by half since 2019.

The practical rule: aim for a skills section that is roughly 60% hard skills and 40% soft skills. The hard skills get you through ATS. The soft skills signal to the human reader that you can function in the role. Listing only hard skills looks robotic; listing only soft skills looks unqualified.

41.4% of recruiters explicitly like seeing soft skills listed in a dedicated section (Novoresume HR survey). The catch: every soft skill you list should be backed by evidence in your experience bullets. "Communication" with no context is noise. "Developed internal training materials used by 120+ employees" is evidence.

Hard Skills to Put on a Resume (by Category)

Hard skills are teachable, measurable, and verifiable abilities: software, certifications, languages, machinery, and methodologies. They are the skills ATS keyword matching cares about most, and they are the ones recruiters scan first. Below are the highest-ROI hard skills by category, pulled from Lightcast 2025 job posting data and LinkedIn Skills on the Rise 2026.

Top hard skills: business and operations

  • Project management (Agile, Scrum, Waterfall, Kanban)
  • Microsoft Excel (pivot tables, VLOOKUP, Power Query)
  • Data analysis (SQL, Tableau, Power BI, Looker)
  • Financial modeling and forecasting
  • Process improvement (Six Sigma, Lean, Kaizen)
  • Vendor and contract management
  • KPI reporting and dashboarding

Top hard skills: marketing and sales

  • SEO and SEM (Ahrefs, Semrush, Google Search Console)
  • Google Analytics 4 and Google Tag Manager
  • Marketing automation (HubSpot, Marketo, Pardot)
  • CRM platforms (Salesforce, HubSpot, Pipedrive)
  • Paid media (Google Ads, Meta Ads, LinkedIn Ads)
  • A/B testing and conversion optimization
  • Email marketing (Mailchimp, Klaviyo, Customer.io)

Top hard skills: healthcare and science

  • Electronic health records (Epic, Cerner, Meditech)
  • Clinical documentation and ICD-10 coding
  • HIPAA compliance
  • Patient assessment and triage
  • Phlebotomy and vital signs
  • Laboratory techniques (PCR, ELISA, HPLC)
  • Certifications (BLS, ACLS, CCRN, PALS)

Top hard skills: finance and accounting

  • GAAP and IFRS accounting standards
  • QuickBooks, NetSuite, SAP
  • Financial statements and variance analysis
  • Cash flow management and forecasting
  • Tax preparation and compliance
  • Budgeting and cost accounting
  • Certifications (CPA, CMA, CFA, EA)

For industry-specific hard skills beyond these categories, see our resume keywords by industry guide (200+ keywords across 10 industries).

Technical Skills to Put on a Resume (Tech Roles)

Technical skills are the subset of hard skills specific to engineering, IT, and data roles: programming languages, frameworks, infrastructure, tools, and methodologies. List them in a dedicated "Technical Skills" section on your resume, then prove them with quantified bullets in your experience section. Below are the technical skills currently appearing most often in US job postings by role category (LinkedIn Workforce Report 2024, Lightcast 2025).

Role category Core technical skills (must-have) High-leverage additions
Software engineer JavaScript/TypeScript, Python, Git, REST APIs, SQL, unit testing React or Vue, Docker, Kubernetes, AWS or GCP, CI/CD pipelines, GraphQL
Backend engineer Python or Go or Java, SQL, PostgreSQL or MySQL, REST APIs, system design Redis, Kafka, gRPC, microservices, Kubernetes, observability (Datadog, New Relic)
Frontend engineer HTML, CSS, JavaScript, TypeScript, React or Vue, Webpack or Vite Next.js, Tailwind, accessibility (WCAG), performance optimization, Storybook
Data analyst SQL, Excel, Python or R, Tableau or Power BI, data cleaning dbt, Snowflake, BigQuery, A/B testing, statistical inference, Looker
Data scientist Python, SQL, pandas, scikit-learn, statistics, ML fundamentals PyTorch or TensorFlow, LLM fine-tuning, MLflow, experiment design, Airflow
DevOps / SRE Linux, Bash, Docker, Kubernetes, Terraform, CI/CD (GitHub Actions or Jenkins) AWS or GCP, Helm, Prometheus, Grafana, Ansible, incident response
IT support Windows and macOS administration, Active Directory, ticketing systems, networking basics PowerShell, Intune or Jamf, Azure AD, MDR tools, ITIL certification
Cybersecurity Network security, SIEM tools, incident response, vulnerability scanning, NIST framework Penetration testing, CISSP or Security+, cloud security (AWS, Azure), SOC 2 audits
Technical skills formatting rule: list exact versions only when the job description asks for them (for example "React 18" or "Python 3.11"). Otherwise the ATS will match the base term and version numbers add clutter. Use the exact capitalization and spelling the job posting uses: "Node.js" not "NodeJS," "PostgreSQL" not "postgres."

AI Skills in 2026: What to List and What to Skip

AI literacy is the #1 fastest-growing skill in job postings according to LinkedIn's Skills on the Rise 2026 report. Jobscan recorded a 30% rise in AI-related hard skill mentions in job descriptions from 2024 to 2025. Listing AI skills is no longer cutting-edge; it is expected.

The problem: 27.2% of workers list AI skills on their resume that they can only perform with significant AI assistance (Novoresume AI and work survey, 1,000 US workers). Recruiters are increasingly aware of this gap and probe AI skills directly in interviews.

List These AI Skills
  • Prompt engineering (with specific use case: "for content generation", "for code review")
  • AI workflow automation (Zapier AI, Make, n8n)
  • LLM API integration (for technical roles)
  • AI-powered analytics tools (Tableau AI, Power BI Copilot)
  • AI Business Strategy (emerging per LinkedIn 2026)
  • Specific platforms with context: "Claude/GPT-4 for [specific task]"
Skip or Upgrade These
  • "ChatGPT" with no context (too generic, every applicant has it)
  • "AI tools" as a standalone skill
  • Machine learning if you cannot explain model choices
  • "AI literacy" without a specific application
  • Any AI skill you cannot demonstrate in a 10-minute interview

How to Choose the Right Skills for Your Resume

The single most effective action is to mirror the language in the job description. ATS systems compare your resume to the job posting. If the posting says "financial modeling" and your resume says "financial analysis," you may not match, even though the terms overlap significantly.

4-Step Skill Selection Process
  1. Pull the job description. Highlight every technical skill, tool, methodology, and credential mentioned.
  2. Check 5 similar postings. Skills appearing in 4 of 5 postings are industry-standard keywords; always include them.
  3. Match your real experience. Only list skills you can discuss for 5+ minutes in an interview. Inflating creates interview problems.
  4. Use the job description's exact language. Use "cross-functional collaboration" if that is their phrase, not "teamwork."

Over 70% of jobs require medium-to-high digital skills (ITIF). Even non-technical roles now expect familiarity with project management software, CRM systems, and collaboration tools. Listing the specific tool name (Salesforce, Jira, HubSpot) outperforms the generic category every time.

Top Skills by Category

These lists are organized by skill category with the most in-demand items first. Use the tables in the next section to filter by industry.

Technical and Computer Skills

SkillTrendCommon Roles
PythonRisingData, Engineering, Finance, Marketing
SQLRisingData, Finance, Operations, Marketing
JavaScript / TypeScriptRisingSoftware Engineering, Web Development
AWS / Azure / GCPRisingEngineering, DevOps, Data
Docker / KubernetesRisingDevOps, Engineering
Excel (advanced)StableFinance, Operations, HR, Marketing
Tableau / Power BIRisingData, Finance, Operations
SalesforceStableSales, Marketing, Customer Success
Google Analytics 4 (GA4)RisingMarketing, E-commerce
HubSpotStableMarketing, Sales
Jira / Asana / Monday.comStableProject Management, Engineering
AutoCAD / SolidWorksStableEngineering, Architecture

Data and Analytics Skills

SkillTrend
Data Analysis / Data AnalyticsRising
Statistical Analysis / Statistical ModelingStable
Machine LearningRising
Data VisualizationRising
A/B TestingStable
ETL (Extract, Transform, Load)Stable
Business Intelligence (BI)Stable
Predictive ModelingRising
dbt (data build tool)Rising
BigQuery / Snowflake / RedshiftRising

Management and Leadership Skills

SkillTrend
Project Management (PMP / Agile / Scrum)Rising
Cross-Functional CollaborationRising
Stakeholder ManagementStable
Budget Management / P&LStable
Strategic PlanningStable
Change ManagementStable
Performance ManagementStable
Risk ManagementRising

Finance and Accounting Skills

SkillTrend
Financial ModelingStable
FP&A (Financial Planning and Analysis)Stable
GAAP / IFRSStable
DCF AnalysisStable
Budget Variance AnalysisStable
SOX ComplianceStable
Risk Management (AML, KYC)Rising
Excel (VLOOKUP, Pivot Tables, Power Query)Stable
ERP Systems (SAP, Oracle, NetSuite)Stable

Marketing Skills

SkillTrend
SEO / SEMStable
PPC / Google Ads / Meta AdsStable
Content MarketingStable
Email MarketingStable
Conversion Rate Optimization (CRO)Rising
Marketing Automation (HubSpot, Marketo)Rising
Attribution ModelingRising
Go-to-Market (GTM) StrategyRising
AI Business StrategyNew in 2026

Healthcare Skills

SkillTrend
HIPAA ComplianceStable
EHR / EMR Systems (Epic, Cerner)Stable
Patient Care / Patient AssessmentStable
Clinical DocumentationStable
Telehealth / Remote Patient MonitoringRising
Value-Based CareRising
Care CoordinationStable
Population Health ManagementRising

HR and Recruiting Skills

SkillTrend
Talent AcquisitionStable
HRIS (Workday, ADP, BambooHR)Stable
Performance ManagementStable
DEI InitiativesRising
Workforce PlanningStable
Compensation BenchmarkingStable
Employee EngagementStable
Skills-Based HiringNew in 2026

Operations Skills

SkillTrend
Process ImprovementStable
Lean / Six SigmaStable
Vendor ManagementStable
SLA ManagementStable
Supply Chain ManagementStable
Capacity PlanningStable
Cost Reduction / EfficiencyStable
ERP Systems (SAP, Oracle)Stable

Skills NOT to Put on a Resume

A bloated skills section is as damaging as a thin one. Generic, expected, or outdated skills dilute the signal and waste the recruiter's time.

Remove ThisReplace WithWhy
Microsoft WordMicrosoft Office Suite (if relevant) or remove entirelyAssumed for any office role; signals outdated thinking
"Hard worker"Evidence in bullets: "Delivered X under Y deadline"Every applicant says it; meaningless without proof
"Team player""Cross-functional collaboration" or specific team outcomeATS does not parse it; humans distrust it
Microsoft Excel (basic)Excel (VLOOKUP, Pivot Tables, Power Query) or remove"Basic" signals the minimum, not a skill worth claiming
Social media (generic)LinkedIn Ads, Instagram, TikTok, or Sprout SocialToo vague; every applicant has "social media"
Flash / SilverlightRemove; technology is deadSignals a resume that has not been updated in a decade
"Fast learner"Certifications earned or specific new skill adoptedNot a skill; a claim any candidate makes

How to Format the Skills Section

ATS systems parse skills sections differently depending on format. Keep it simple to ensure full extraction.

Option 1: Horizontal List

Best for: most roles, ATS-heavy application systems

Python | SQL | Tableau | Excel | Stakeholder Management | Agile | JIRA
Option 2: Grouped by Category

Best for: technical roles, senior roles with many skill types

Technical: Python, SQL, dbt
Analytics: Tableau, Power BI
Tools: JIRA, Confluence
Option 3: Skills + Proficiency

Best for: roles with explicit proficiency screening (language levels, tool certs)

Python (Advanced) | Spanish (B2) | Excel (Expert)
ATS formatting rule: Do not put your skills inside a table or multi-column text box in Word or Google Docs. Many ATS systems cannot parse table cells reliably. Use a simple single-column list or pipe-separated values.

Placement: for most professionals with 2+ years of experience, the skills section belongs after your summary and before your work experience. For career changers and recent graduates, place it higher; it may be the strongest section on the page.

7 Common Skills Section Mistakes

1. Listing Too Many

25-30 skills is the effective ceiling. More than 35 signals padding, and both ATS systems and human reviewers penalize it.

2. Listing "Beginner" Proficiency

If a skill is beginner-level, ask whether it belongs on the resume at all. Listing it as "beginner" invites the recruiter to wonder if you are job-ready.

3. Duplicating Experience

The skills section names the capability. The experience section proves it. Use one to validate the other; do not repeat identical phrases in both.

4. No Job-Specific Tailoring

54% of candidates do not tailor resumes to the job description (The Interview Guys). A static skills section that never changes is the clearest sign of a mass-apply approach.

5. Claiming Unprovable Skills

27.2% of workers list AI skills they can only perform with significant assistance (Novoresume). Interviews expose this instantly.

6. Keyword Stuffing

Adding 60 keywords in tiny white text or pasting job descriptions verbatim. Modern ATS and AI screeners detect this and trigger automatic rejection at companies that check.

7. Wrong Placement for Your Career Stage

Senior professionals who lead with the skills section look like they are hiding a thin work history. Recent graduates who bury the skills section below three pages of marginal experience waste their strongest asset. Match placement to where your value is most concentrated.

Copy-Paste Skills Sections by Industry

Every block below is a complete, ready-to-adapt skills section. Copy the one closest to your field, then swap in the tools and credentials named in your target job posting. The sub-heading labels matter as much as the skills themselves: they are what makes a parser and a recruiter read the section in the same order.

Software Engineer / Data Engineer

Technical Skills Section: Software Engineer

Languages: Python, Java, TypeScript, SQL, Go

Frameworks & Tools: React, Node.js, Spring Boot, FastAPI, Docker, Kubernetes

Cloud & Data: AWS (EC2, S3, Lambda, RDS), PostgreSQL, Redis, Kafka, Spark

Practices: CI/CD, Agile/Scrum, test-driven development, code review, system design

AI/ML Tools: LangChain, OpenAI API, Hugging Face, PyTorch (familiarity)

Data Analyst

Skills Section: Data Analyst

Analysis & Modeling: SQL (advanced), Python (pandas, NumPy, scikit-learn), R (intermediate), statistical analysis, regression modeling, A/B testing

Visualization: Tableau, Power BI, Matplotlib, Seaborn, Excel (advanced, pivot tables, VBA)

Data Engineering: dbt, Snowflake, BigQuery, Airflow (familiarity), data pipeline maintenance

Marketing Manager

Skills Section: Marketing Manager

Digital Marketing: SEO, paid search (Google Ads), paid social (Meta, LinkedIn), email marketing, content strategy

Analytics: Google Analytics 4, Semrush, HubSpot, Marketo, Salesforce CRM, A/B testing

Content: Copywriting, brand voice, editorial calendar management, campaign briefing

Operations: Demand generation, marketing operations, budget management, cross-functional collaboration

Project Manager

Skills Section: Project Manager

Methodologies: Agile, Scrum, Waterfall, Kanban, PRINCE2

Tools: Jira, Asana, MS Project, Smartsheet, Confluence, Monday.com

Project Skills: Risk management, scope management, stakeholder reporting, resource planning, budget oversight

Credentials: Project Management Professional (PMP), Certified Scrum Master (CSM)

Healthcare / Clinical

Skills Section: Registered Nurse (ICU)

Clinical Skills: Mechanical ventilation, hemodynamic monitoring, arterial line management, CRRT, vasopressor titration, rapid assessment

Technology: Epic EMR, Cerner, Meditech, Pyxis medication dispensing

Certifications: Registered Nurse (RN, active), Basic Life Support (BLS), Advanced Cardiac Life Support (ACLS), Critical Care Registered Nurse (CCRN)

Operations / Supply Chain

Skills Section: Operations Manager

Operations: Process improvement, Lean/Six Sigma, KPI development, cost reduction, vendor management

Supply Chain: Inventory management, demand forecasting, warehouse management, logistics coordination, ERP systems (SAP, Oracle)

Analytics: Excel (advanced), Power BI, Tableau, SQL (intermediate)

Credentials: Lean Six Sigma Green Belt, APICS CSCP (certified supply chain professional)

Finance and Accounting

Skills Section: Financial Analyst

Financial: Financial modeling, forecasting, variance analysis, budgeting, month-end close, GAAP reporting

Systems: SAP, Oracle NetSuite, QuickBooks, Hyperion, Excel (advanced, pivot tables, macros)

Analytics: SQL, Power BI, Tableau, scenario modeling

Credentials: Certified Public Accountant (CPA), Chartered Financial Analyst (CFA Level II candidate)

Sales

Skills Section: Account Executive

Sales Skills: Pipeline management, consultative selling, territory planning, contract negotiation, quota attainment, upselling and renewals

Tools: Salesforce, HubSpot CRM, Outreach, Gong, ZoomInfo, LinkedIn Sales Navigator

Methodologies: MEDDIC, Challenger Sale, SPIN Selling, solution selling

Reporting: Forecast accuracy, win/loss analysis, sales dashboards

Education

Skills Section: Classroom Teacher

Instruction: Curriculum design, differentiated instruction, lesson planning, formative and summative assessment, IEP implementation

Classroom: Behaviour management, restorative practices, parent communication, small-group intervention

Technology: Google Classroom, Canvas LMS, PowerSchool, Seesaw, Nearpod

Credentials: State teaching license (active), ESL endorsement, Special Education certification

Engineering (Mechanical / Civil)

Skills Section: Mechanical Engineer

Design: SolidWorks, AutoCAD, CATIA, finite element analysis (FEA), GD&T, tolerance stack-up

Analysis: ANSYS, MATLAB, thermal analysis, failure mode and effects analysis (FMEA)

Manufacturing: DFM, injection molding, CNC machining, tolerance analysis, prototyping

Credentials: Professional Engineer (PE), Six Sigma Green Belt

Customer Service / Support

Skills Section: Customer Support Specialist

Support: Ticket triage, escalation management, SLA adherence, root-cause troubleshooting, knowledge-base authoring

Platforms: Zendesk, Intercom, Freshdesk, Salesforce Service Cloud, Jira Service Management

Metrics: CSAT, NPS, first-response time, first-contact resolution

Languages: English (native), Spanish (professional working proficiency)

Before and After: Skills Section Makeovers

The difference between a skills section that gets filtered and one that ranks is rarely the number of skills. It is specificity and grouping. Both makeovers below keep roughly the same skill count.

Makeover 1: Marketing Manager

Marketing Manager Skills: Before and After

Before:

Skills: Microsoft Office, communication, social media, creative thinking, teamwork, marketing, customer service, analytical skills, leadership, Google

After:

Digital Marketing: SEO (on-page, technical), Google Ads, Meta Ads Manager, LinkedIn Campaign Manager, email marketing (HubSpot)

Analytics: Google Analytics 4, Semrush, Looker, A/B testing, conversion rate optimization

Operations: Campaign management, editorial calendar, budget tracking, cross-functional project coordination

Makeover 2: Data Analyst

Data Analyst Skills: Before and After

Before:

Skills: Data analysis, Excel, Python, critical thinking, attention to detail, reporting, SQL, statistics, PowerPoint, problem solving

After:

Analysis & Modeling: SQL (advanced), Python (pandas, NumPy, scikit-learn), R (intermediate), statistical analysis, regression modeling, A/B testing

Visualization: Tableau, Power BI, Matplotlib, Seaborn, Excel (advanced, pivot tables, VBA)

Data Engineering: dbt, Snowflake, BigQuery, Airflow (familiarity), data pipeline maintenance

Skills for a Resume by Experience Level

The same job title calls for a different skills mix depending on where you are in your career. Entry-level candidates are screened on tools and trainability; senior candidates are screened on scope and judgement.

Level Weight toward What to lead with What to cut
Student / entry level 70% hard, 30% soft Named tools, coursework-backed technical skills, certifications in progress, language proficiency Leadership, strategy, "stakeholder management" with nothing behind it
Mid career (3 to 8 years) 60% hard, 40% soft Depth in a specialism, the platforms you own, cross-functional collaboration Baseline software (Word, email), skills from a career stage you have outgrown
Senior / lead 50% hard, 50% soft Scope words (roadmap ownership, budget, vendor selection), mentoring, the technical skills you still practise Junior tooling detail, long tool inventories with no ownership signal
Career changer 65% hard, 35% soft Transferable technical skills named the way the new industry names them, plus new certifications Industry-specific jargon from the field you are leaving

The career-changer row is the one people get wrong most often. If you managed budgets in nonprofit work and you are moving into operations, write "budget management" and "vendor negotiation", not "grant stewardship". Same skill, different keyword, and only one of them matches the posting.

How Many Skills to List and Where to Put Them

List 8 to 12. Below 6 the section looks thin and gives the parser too little to match; above 15 it reads as padding and dilutes the keywords that matter. If you have more than 12 genuinely relevant skills, group them under sub-headings so the section stays scannable.

Your situation Where the skills section goes Why
Technical role, any level Directly under the summary, above work experience The tool stack is the primary screening criterion; make it the first thing after the summary
Experienced, staying in the same field After work experience Your job history is the stronger signal; skills confirm rather than lead
Career changer Directly under the summary Your recent titles work against you; transferable skills need to land before the reader sees the old industry
Student or new graduate Under education, above any experience Skills and coursework carry more weight than a short work history

Proficiency levels: when to include them

Add a proficiency qualifier only where it is genuinely informative and verifiable: languages ("Spanish, professional working proficiency"), and technical skills where the gap between basic and advanced is large ("Excel, advanced: pivot tables, Power Query, VBA"). Never rate soft skills. A five-star graphic next to "communication" tells a recruiter nothing and does not parse.

How Resume Optimizer Pro Extracts and Matches Skills

Manually comparing your skills against a job posting is useful but slow, and it is easy to miss synonyms and keyword variants. Resume Optimizer Pro parses the job description for every explicit and implicit skill requirement, then compares them against your resume at the keyword level.

The engine scores the skills section on four dimensions: coverage (how many of the posting's named skills appear on your resume), phrasing match (whether you used the posting's exact term or a synonym a parser will not connect), placement (whether skills also appear in your work experience bullets, which is what separates a claimed skill from an evidenced one), and parse integrity (whether the section survives text extraction, or whether tables, columns, and icons scramble it).

The most common failure we see is the phrasing gap rather than a missing skill. A resume says "customer relationship management" and the posting says "Salesforce"; a resume says "data visualisation" and the posting says "Tableau". The skill is real and the match is still missed, because keyword matching does not reason about synonyms the way a human reader does.

The output is a match percentage plus a prioritized list of skills to add, with the exact phrasing taken from the posting. So you do not just learn that a skill is missing; you learn the precise term to add and where to put it.

Frequently Asked Questions

Two different numbers get confused here. In the dedicated skills section, list 8 to 12, grouped under sub-headings. Across the resume as a whole, including your work experience bullets, industry benchmarks recommend 15 to 25 total keywords: roughly 10-15 industry-specific and 5-8 job-specific. A skills section below 6 gives the parser too little to match; above 15 it reads as padding and dilutes your strongest entries.

Only when they add meaningful information. Language proficiency levels (B2, C1, Native) and certification levels (AWS Associate vs. Professional) are worth noting because they carry specific meaning. Generic "beginner/intermediate/advanced" bars for most skills add noise and invite scrutiny. If you are listing a skill, the implicit assumption is professional working proficiency.

Focus on tools and technologies used in coursework, personal projects, or internships. A personal project using Python, Tableau, or HubSpot is evidence of a skill. Transferable soft skills (communication, research, organization) backed by academic or volunteer examples are also valid. Specificity matters: "Python (data cleaning and visualization via Pandas/Matplotlib)" beats "Python."

For most experienced professionals: after your summary, before work experience. This gives ATS systems a clear keyword section to parse and gives recruiters an instant role-fit signal. For career changers and recent graduates whose skills are their primary qualification, place the section immediately after the summary or use a skills-first resume format.

Yes, but with specificity. "ChatGPT" alone is too generic. Frame AI tools by application: "Prompt engineering for marketing copy generation," "GPT-4 API integration for automated reporting," or "AI-assisted data analysis with Python and OpenAI API." AI literacy is the #1 fastest-growing skill in job postings (LinkedIn Skills on the Rise 2026), so relevant AI skills belong on most 2026 resumes.

LinkedIn's Skills on the Rise 2026 report names AI literacy, cross-functional collaboration, adaptability, AI Business Strategy, go-to-market strategy, prompt engineering, risk and compliance expertise, and public speaking as the top rising skills. In hard technical skills, Python, SQL, cloud platforms (AWS/Azure/GCP), and data visualization (Tableau, Power BI) continue to lead employer demand. NACE Job Outlook 2026 identifies problem-solving (89% of employers), teamwork (78%), written communication (70%+), and analytical skills as the top attributes employers screen for in new graduates.

Yes, and it is the recommended approach. Mirroring the exact language from the job description is the most reliable way to pass ATS keyword filtering. The key constraint is honesty: only list skills that reflect your actual capability. Make sure your experience bullets demonstrate each skill you claim; ATS systems increasingly flag resumes that mirror job descriptions without supporting evidence in the work history section.

Hard skills are teachable, measurable, and usually tied to a tool, language, or credential: Python, Salesforce, CPA, mechanical ventilation. Soft skills describe how you work: collaboration, adaptability, stakeholder communication. Hard skills carry almost all of the ATS keyword match, which is why the 60/40 split in this guide favours them. For a fuller breakdown of when each type belongs where, see our guide to soft skills vs hard skills.

Avoid it. Tables, text boxes, and multi-column layouts are the most common reason a skills section parses badly: extraction can read across rows instead of down columns, producing scrambled output like "Python Tableau SQL Excel advanced R". Use plain labelled lines instead, in the format shown in the copy-paste sections above. Icons and star ratings carry no text at all and are simply dropped.

Take the skills named in the posting's requirements section first, in the posting's own wording, and only those you can actually evidence. Then check for synonym gaps: if the posting says "Tableau" and your resume says "data visualisation", you will not match even though the skill is real. Skills repeated in both the summary and the requirements are the highest priority. Our guide on aligning skills with job descriptions covers the full process.