Anti-Fraud Spec II - Cientista de Dados Pleno
Tasks
- Build training validation and monitoring pipelines
- Contribute to data science and MLOps practices
- Define and track model performance metrics
- Deploy and monitor models in production
- Develop statistical and machine learning models
- Document technical work and present results
- Monitor model drift performance and stability
- Perform exploratory data analysis
- Prepare and clean large volume datasets
- Translate business problems into analytics solutions
Perks/Benefits
- Childcare assistance
- Dental insurance
- Gympass
- Life balance program
- Life insurance
- Meal allowance
- Medical insurance
- Retirement plan
- Transportation allowance
Skills/Tech-stack
ADASYN | CI/CD | CatBoost | Class Weights | Cross-validation | Data Drift | Data drift monitoring | Databricks | Docker | Drift monitoring | F1-score | Feature Engineering | Git | Gradient boosting | KS | Kubernetes | LIME | LightGBM | Logistic Regression | MLOps | Machine Learning | Model Governance | Model Interpretability | Model Monitoring | Model Risk Management | Model risk | NumPy | Oversampling | PR AUC | Pandas | Precisión | Probability | PySpark | Python | REST APIs | ROC-AUC | Random Forest | Recall | Risk Management | SHAP | SMOTE | SQL | Spark | Statistics | Threshold Optimization | Undersampling | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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