How to Write a Data Analyst Resume That Scores Above 80

A score of 80 or above on a resume screen means you're in the top tier of applicants. For data analyst roles, hitting that mark requires a specific combination of keywords, structure, and quantified impact. Here's exactly how to get there. The Keywords That Matter Data analyst job postings consistently require these skills. If they're missing from your resume, your score drops immediately: SQL (mentioned in 95% of postings), Python or R (85%), Tableau or Power BI (80%), Excel (75%), statistical analysis (70%), data visualization (65%), ETL (50%), A/B testing (40%). Include the exact terms used in the job posting. If they say "Tableau," don't just say "data visualization tools." The Structure Contact Information: Name, email, phone, LinkedIn, location (city/state only). Professional Summary: 2-3 sentences. "Data analyst with 4 years of experience in e-commerce analytics. Specialize in customer behavior analysis and revenue attribution using SQL, Python, and Tableau. Reduced customer churn by 18% through predictive modeling." Experience: 3-5 bullets per role. Every bullet: Action verb + what you analyzed + business impact with numbers. Good: "Built automated reporting dashboard in Tableau tracking $12M in quarterly revenue across 3 product lines, reducing manual reporting time by 15 hours per week." Bad: "Created dashboards for the team." Skills: Organized by category. Data Tools: SQL, Python, R. Visualization: Tableau, Power BI, Looker. Analysis: Statistical modeling, A/B testing, regression analysis. Education: Degree, school, graduation year. Add relevant coursework only if you're early career. Certifications: Google Data Analytics, Tableau Desktop Specialist, or AWS Data Analytics if you have them. Score your data analyst resume at aenview.com/careers/resume-score/data-analyst/ and see exactly where you stand.