40+ Resume Keywords for Data Analysts

Essential data analytics keywords for ATS optimization. Covers tools, techniques, and domain-specific terms that hiring managers search for.

Data analyst roles and ATS

Data analyst positions have exploded in demand, but so has competition. Every major company now has data teams, and they all use ATS to filter the flood of applications. The right keywords can mean the difference between an interview and silence.

Technical tools and languages

SQL (the most important keyword), Python, R, Excel (advanced/VBA), Tableau, Power BI, Looker, Google Analytics (GA4), BigQuery, Snowflake, Databricks, dbt, Jupyter Notebook, Pandas, NumPy, scikit-learn.

Statistical and analytical methods

Statistical analysis, regression analysis, hypothesis testing, A/B testing, predictive modeling, machine learning, data mining, time series analysis, correlation analysis, cluster analysis, sentiment analysis, forecasting.

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Data engineering and infrastructure

ETL/ELT, data pipelines, data warehousing, data modeling, dimensional modeling, star schema, data governance, data quality, data cleaning/wrangling, API integration, cloud platforms (AWS, GCP, Azure).

Business and communication skills

Data storytelling, stakeholder communication, dashboard design, KPI development, business intelligence, executive reporting, requirements gathering, cross-functional collaboration, data-driven decision making.

Match your resume to the role

Data analyst roles vary widely — a marketing analytics role needs different keywords than a financial analyst position. ATSBoost matches your resume against the specific job description, so you know exactly which tools and techniques to highlight.