Data analyst resumes must demonstrate comfort with both technical and business sides — translating numbers into decisions.
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ATS systems scan for specific keyword matches. Include as many of these skills as you genuinely have — the closer you match the job description, the higher your ATS score.
Start every bullet point with a strong action verb. These are the highest-impact verbs for Data Analyst resumes — specific, measurable, and ATS-approved.
Follow this structure to ensure recruiters find what they need — and ATS systems score your resume correctly.
Name, phone, professional email, LinkedIn URL, and city/state. For tech roles, include your GitHub URL and portfolio link — many ATS systems parse these.
2-3 sentences: your years of experience as a Data Analyst, your 2-3 signature strengths (e.g. SQL, Python), and your career goal. Rewrite this for every application — it's the first thing an ATS and recruiter both read.
Company, title, dates, location — then 3-5 bullet points per role. Start every bullet with a strong verb like "Analyzed" or "Modeled" and quantify every outcome. Don't just describe tasks — prove impact with numbers, percentages, or dollar amounts tied to skills like SQL, Python, Excel.
A dedicated skills block is the primary ATS filter for Data Analyst roles. Include: SQL, Python, Excel, Tableau, Power BI, Statistics, ETL, Google Analytics. Mirror the exact keyword phrasing from each job description — "React.js" and "ReactJS" can be scored differently.
Degree, institution, graduation year. In Technology, education goes after work experience once you have 3+ years of relevant professional history.
Certifications are a meaningful differentiator for Data Analyst positions in Technology. List the full certification name, the issuing body, and the year obtained. Active credentials with expiration dates should include the renewal date — employers in Technology actively verify these.
Include specific tools. Use metrics: 'reduced report generation time by 60%' ranks better than vague claims.
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