Lead Fraud Data Scientist
USD 140K-199K (estimate) Senior-level Full Time
Tasks
- Build fraud detection models
- Collaborate with product and engineering
- Conduct A/B tests
- Create fraud dashboards
- Define fraud machine learning strategy
- Deploy and monitor models
- Engineer fraud features
- Integrate ML scores with rule engines
- Investigate emerging fraud patterns
- Mitigate credit and lending fraud
- Perform clustering and outlier detection
- Train and validate models
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | Algorithmic Fairness | Azure | B testing | CI/CD | CatBoost | Clustering | GCP | Graph Neural Networks | Imbalanced Data | Isolation Forest | K-Means | K-Nearest Neighbors | K-nearest | LIME | Lasso Regression | LightGBM | Logistic Regression | Looker | MLOps | Machine Learning | Nearest neighbors | Neo4j | NetworkX | Neural Networks | Outlier Detection | Pandas | Python | Ridge regression | 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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