Data Scientist Resume Example
Data science resumes need to balance technical depth with business impact. Hiring managers want to see that you can build models, but they care even more about what those models did for the company. Show the math and the money.
Sample resume
This is an AI-assisted example. Use it as a starting point, not a copy-paste template. Your resume should reflect your actual experience and numbers.
Daniel Park
Seattle, WA | daniel.park@email.com | (555) 789-2345 | linkedin.com/in/danielpark | github.com/dpark-ml
Summary
Data scientist with 5 years of experience building ML systems that drive revenue decisions. Deployed a recommendation engine serving 8M users at a Fortune 500 retailer. Published 2 papers on NLP methods at ACL. Comfortable owning a project from exploratory analysis through production deployment.
Experience
Senior Data Scientist, Amazon
Seattle, WA | Mar 2023 - Present
- Built a product recommendation model (collaborative filtering + deep learning) that increased click-through rate by 17% across 8M monthly active users, generating an estimated $34M in incremental annual revenue
- Designed and ran 12 A/B tests on search ranking algorithms, identifying a re-ranking approach that improved conversion by 9%
- Developed an NLP pipeline using BERT fine-tuning to classify 500K+ daily customer reviews into 23 intent categories with 91% accuracy
- Mentored 3 junior data scientists on experiment design and model evaluation best practices
Data Scientist, Nordstrom
Seattle, WA | Jun 2021 - Feb 2023
- Built a customer churn prediction model (XGBoost) that identified 14,000 at-risk accounts worth $18M in annual spend, enabling a retention campaign that saved $4.2M
- Created a demand forecasting pipeline in Python (Prophet + custom features) that reduced overstock by 22% across 3 product categories
- Automated weekly KPI reporting with Airflow and Looker, replacing 15 hours/week of manual Excel work
Research Assistant, University of Washington
Seattle, WA | Sep 2019 - May 2021
- Published 2 papers on transformer-based text summarization at ACL 2020 and EMNLP 2021
- Built a text summarization model that outperformed the baseline ROUGE-L score by 8 points on the CNN/DailyMail dataset
Education
M.S. Computer Science (Machine Learning), University of Washington
2019 - 2021 | GPA: 3.9
B.S. Mathematics, UCLA
2015 - 2019
Skills
Languages: Python, R, SQL, Scala ML/AI: TensorFlow, PyTorch, scikit-learn, XGBoost, Hugging Face Transformers, spaCy Tools: Airflow, Spark, AWS SageMaker, Docker, MLflow, Looker, Jupyter Methods: Deep Learning, NLP, Recommendation Systems, A/B Testing, Time Series Forecasting, Bayesian Statistics
Key skills for data scientist resumes
These are the skills that show up most often in data scientist job descriptions. Include the ones you actually have experience with.
ATS tips for data scientist resumes
- •List ML frameworks and libraries explicitly: TensorFlow, PyTorch, scikit-learn, XGBoost, Hugging Face. Recruiters and ATS systems filter on these names.
- •Quantify model performance with real metrics: accuracy, F1 score, AUC-ROC, RMSE. 'Built a classification model' is vague. 'Built a classification model with 94% precision and 89% recall' is specific.
- •Include the business outcome alongside the technical work. 'Reduced customer churn by 12% ($2.4M annual impact)' connects the model to revenue.
- •Mention the scale of data you work with. '50M row clickstream dataset' or 'trained on 200K labeled images' gives reviewers a sense of your experience level.
- •If you have published papers or open-source contributions, add a separate section for them. Academic credibility matters in data science hiring.
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