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These keywords appear most frequently in data analyst job descriptions. Missing even a few can drop your ATS score below the screening threshold.
Hard and soft skills that data analyst ATS systems look for
Common mistakes that cause data analyst resumes to fail ATS screening
Lead with SQL - it's the #1 required skill in 85% of data analyst job postings
Specify BI tools exactly: 'Tableau Desktop', 'Power BI', 'Looker Studio' - not generic 'data visualization tools'
Include both 'Data Analyst' and 'Business Analyst' if applicable - many JDs use both
Quantify reports: 'built dashboard tracking $15M revenue pipeline', 'automated 10 weekly reports'
Mention data scale: 'analyzed datasets of 50M+ rows' shows you can handle real-world data
Include domain context: 'e-commerce analytics', 'financial reporting', 'marketing analytics'
The most critical ATS keywords for data analysts are: SQL (required by 85% of roles), Excel, Python or R, a BI tool (Tableau, Power BI, or Looker - whichever the company uses), data visualization, KPIs, and A/B testing. Always mirror the exact tool names from the job description.
Structure your resume with a Skills section listing all technical tools, use metrics in every bullet point ('built X dashboard used by Y stakeholders', 'reduced reporting time by Z%'), include the industry domain, and list both full tool names and abbreviations. Use ATS CV Checker to compare your resume against each specific job description.
Yes, even if it's a secondary skill. Python (Pandas, NumPy) is increasingly expected even for business-focused analyst roles. If you know it, list it. If you're learning it, you can add 'Python (learning)'. Roles that require heavy ML work are typically called Data Scientists, not Data Analysts.
Data Analyst resumes emphasize: SQL, Python/R, statistical analysis, data visualization tools, and working with raw data. Business Analyst resumes focus on: requirements gathering, process mapping, stakeholder management, JIRA, and business documentation (BRD, use cases). Many roles overlap - use the job description as your guide.
Build a portfolio of 3–5 SQL/Python projects, get the Google Data Analytics Certificate, and apply to junior/entry-level roles. On your resume, list course projects with real datasets (Kaggle, public data), certifications, and any data work from previous non-analyst roles. ATS CV Checker helps you tailor each application to the specific JD.
Guides to help you pass ATS screening faster