Lead Fraud Data Scientist
Guadalajara, Monterrey, Queretaro, CDMX
R
MXN 934K-1300K (estimate) Senior-level Full Time
Tasks
- Analyze emerging fraud patterns
- Build fraud detection models lifecycle
- Cluster user behavior
- Define fraud machine learning strategy
- Deploy models in cloud
- Design credit lending fraud mitigation models
- Detect application fraud
- Detect loan default fraud
- Detect outliers
- Detect synthetic identity fraud
- Establish machine learning best practices
- Integrate machine learning scores with rule engines
- Maintain dashboards
- Measure fraud detection impact
- Mentor junior data scientists
- Monitor model performance
- Perform A/B testing
- Perform data exploration
- Perform feature engineering
- Run network analysis
- Train validate deploy monitor models
- Visualize false positive rate
- Visualize fraud loss rate
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | Algorithmic Fairness | Azure | B testing | CI/CD | CatBoost | Clustering | GCP | Imbalanced Data | Isolation Forest | K-Means | K-Nearest Neighbors | K-nearest | LIME | Lasso | LightGBM | Logistic Regression | Looker | MLOps | Machine Learning | Model Explainability | Nearest neighbors | Outlier Detection | Pandas | Python | Ridge | SHAP | SQL | Sampling techniques | Scikit-learn | Statistics | Tableau | Vertex AI | XGBoost
Education
N/A
Roles
Data Scientist | Lead | Lead Data | Lead Data Scientist | Scientist
Regions
Countries
States
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