Resume Checker for Data Analysts

Data analyst roles get flooded with applications from bootcamp grads, career changers, and experienced analysts alike. ATS is the first filter. Common data analyst resume issues: • Listing "data analysis" generically instead of naming specific tools • Not showing SQL proficiency prominently • Missing visualization tool experience (Tableau, Power BI, Looker) • No quantified business impact from analysis work

Our AI scans for: • Languages: SQL, Python, R — be specific about libraries (pandas, NumPy, matplotlib) • Visualization: Tableau, Power BI, Looker, Google Data Studio, Excel charts • Databases: MySQL, PostgreSQL, BigQuery, Snowflake, Redshift • Methods: statistical analysis, A/B testing, regression, cohort analysis, forecasting • Tools: Excel (pivot tables, VLOOKUP, macros), Google Sheets, Jupyter notebooks • Concepts: ETL, data cleaning, data modeling, KPIs, dashboards, reporting

1. Lead with a skills section listing tools by category 2. Quantify every analysis: "Identified $500K revenue opportunity through churn analysis" 3. Describe the full analysis lifecycle: data collection → cleaning → analysis → insight → action 4. Mention stakeholders served: executives, marketing, product, operations 5. Include portfolio links to dashboards or analysis projects 6. Show progression in data complexity and business impact

Match your resume to the exact role title: Data Analyst: • SQL mastery, dashboard building, ad-hoc analysis, Excel proficiency • Focus on descriptive analytics and reporting Business Intelligence Analyst: • BI tool expertise (Tableau, Power BI), data warehousing, ETL pipelines • Focus on self-service analytics and data infrastructure Data Scientist: • Machine learning, statistical modeling, Python/R, experimentation • Focus on predictive analytics and advanced modeling