[Your Name]
Data Scientist · Machine Learning & Experimentation
[City] · [email@example.com] · [Phone] · [linkedin.com/in/yourname]
Summary
Data scientist with 4 years building models that change business decisions. Experienced across the full cycle, from framing the problem and engineering features to deploying, monitoring and explaining results.
Skills
Python (scikit-learn, pandas) · SQL · Statistical modelling · Machine-learning evaluation · Experiment design · Feature engineering · MLflow / model deployment · Data storytelling
Experience
Data Scientist2022 – Present
[Company], [City]
- Built a churn-prediction model (AUC 0.86) that helped retention teams save 9% more customers.
- Designed and analysed 20+ A/B tests, setting the team's standard for sample sizes.
- Deployed models behind an API with drift monitoring and monthly retraining.
Data Analyst2020 – 2022
[Company], [City]
- Built a demand forecast that reduced stock-outs by 15% across 200 stores.
- Presented monthly insights to leadership, turning model results into actions.
Projects
Customer churn prediction
Python, scikit-learn, XGBoost, SHAP
- Trained and compared 4 models on 100k customer records; best model reached AUC 0.86.
- Explained top churn drivers with SHAP and turned them into 3 retention actions.
Support ticket classifier (NLP)
Python, Hugging Face Transformers, FastAPI
- Fine-tuned a text model to route support tickets into 8 categories with 91% accuracy.
- Served it through a FastAPI endpoint with a Docker image and a simple monitoring log.
Sales forecasting
Python, Prophet, SQL
- Forecast weekly demand for 200 products, lowering error (MAPE) from 18% to 11% versus the old method.
Education
M.Sc, Statistics / Data Science — [University], 2020
Certifications
- Microsoft Certified: Azure Data Scientist Associate
- TensorFlow Developer Certificate