Data Scientist CV Example
Professional data scientist CV example with recruiter-tested sections you can customise in minutes.
Example only
All personal details and career history in this example are fictional. Customise this CV with your own real information before applying.
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Skills
Certifications
TensorFlow Developer Certificate
TensorFlow
2023-06-01
IBM Data Science Professional Certificate
IBM
2022-06-01
Languages
English (Native)
German (Conversational)
Ava Brooks
Data Scientist
6 years of experience building predictive models, recommendation engines, and business forecasting solutions.
Experience
Senior Data Scientist
Quant Bloom, Full-time
2020-06-01 – Present
San Francisco, CA, US
Predictive modeling for personalization and churn — XGBoost propensity models, feature-store governance, and causal inference.
- Led predictive modeling initiatives for personalization and churn prevention
- Built propensity models with XGBoost and calibrated probabilities, increasing precision of retention campaigns by 24%.
- Created a feature store governance process with versioned transformations to ensure training-serving consistency.
- Presented causal inference findings to product leadership, reshaping pricing experiments to avoid Simpson paradox artifacts.
Data Scientist
Echo Retail Intelligence, Full-time
2018-05-01 – 2020-05-01
Boston, MA, US
ML solutions and experimentation — Prophet demand forecasting, SHAP interpretability, and MLflow productionization.
- Developed machine learning solutions and experimentation frameworks
- Implemented demand forecasting models using Prophet and hierarchical reconciliation for region-level planning.
- Designed SHAP-based model interpretability dashboards that improved stakeholder trust for automated recommendations.
- Partnered with engineering to productionize notebook prototypes into batch scoring jobs with MLflow tracking.
Junior Data Scientist
Vantage Pattern, Full-time
2016-04-01 – 2018-04-01
Barcelona, Spain
Model development and data exploration — transformer text features, imbalanced-data evaluation, and reproducible reporting.
- Supported model development and data exploration workflows
- Engineered text features with sentence transformers for support ticket triage, reducing manual routing load.
- Conducted error analysis on class-imbalanced datasets and introduced stratified evaluation protocols.
- Automated model evaluation reports in Jupyter and Weights & Biases for reproducible experiment reviews.
Education
Data Science, Master of Science
University of Michigan
2018-09-01 – 2020-06-01
Graduate studies in data science covering advanced theory, applied projects, and research methods. Coursework emphasized Python, Pandas, Scikit-learn and professional communication.
CV writing guide
- Link model outcomes to business impact and decision quality.
- Demonstrate rigorous experimentation and leakage-aware validation.
- Show ability to communicate uncertainty and trade-offs clearly.
- TensorFlow Developer Certificate
- IBM Data Science Professional Certificate
- AWS Certified Machine Learning - Specialty