Data Scientist Resume Example
Create a data scientist resume with model performance metrics, business impact, and technical depth. Examples for ML engineers and applied scientists.
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Developed a churn prediction model (XGBoost) with 92% AUC, reducing annual customer loss by $1.8M
Built and deployed a real-time recommendation engine serving 500K daily users, increasing click-through rate by 35%
Designed A/B testing framework used by 3 product teams, improving experiment velocity by 4x
Led data pipeline migration to Spark on AWS EMR, reducing nightly batch processing from 8 hours to 45 minutes
Published internal research on transformer-based NLP models, adopted by 2 other teams for production use
Tips for Your Data Scientist Resume
Always include model performance metrics (AUC, F1, RMSE) alongside business impact
Show the full ML lifecycle: data collection, feature engineering, training, deployment, monitoring
Include tools and frameworks: Python, PyTorch, TensorFlow, Spark, SQL
Explain business impact in dollars or percentages, not just technical performance
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