Quick answer
What keywords should I put on my data science resume?
Top data science resume keywords for 2026: Python, SQL, TensorFlow, PyTorch, Scikit-learn, Tableau, Power BI, A/B Testing, Statistical Analysis, and Machine Learning. For Data Analyst roles, prioritize SQL, Excel (Advanced), Google Analytics, and Data Visualization. Always quantify impact: "Modeled customer churn prediction achieving 89% accuracy, saving $2.3M annually." Certifications like Google Data Analytics or AWS ML Specialty significantly boost ATS scores.
Data Scientist
View Resume Format →Hard Skills (15)
Soft Skills (6)
ATS Match Keywords (7)
Certifications (3)
Power Action Verbs
“Modeled customer churn prediction achieving 89% accuracy, saving $2.3M in annual revenue”
“Predicted demand patterns using time-series analysis, reducing inventory waste by 25%”
“Visualized complex datasets into executive dashboards used by C-suite for strategic decisions”
Data Analyst
View Resume Format →Hard Skills (10)
Soft Skills (6)
ATS Match Keywords (6)
Certifications (2)
Power Action Verbs
“Analyzed customer behavior data across 500K+ records, identifying 3 key growth segments”
“Quantified marketing campaign ROI across 5 channels, redirecting $1M to highest-performing”
BI Analyst
View Resume Format →Hard Skills (10)
Soft Skills (6)
ATS Match Keywords (6)
Certifications (2)
Power Action Verbs
“Developed self-service BI dashboards adopted by 150+ business users across 4 departments”
“Streamlined monthly reporting from 5-day manual process to automated same-day delivery”
Job-description workflow
Match language without inventing experience
- 1. Highlight: mark repeated skills, tools, credentials, and outcomes in the target description.
- 2. Verify: keep only terms you can support with work, projects, education, or training.
- 3. Prove: place the strongest terms inside natural bullets that explain action, context, and result.