Vice President – Credit Risk Data Science, Business Banking Risk Modeling
Wilmington, DE, United States
USD 241K-285K (estimate) Executive-level Full Time
Tasks
- Align partners on implementation documentation lineage and lifecycle
- Apply transformer based approaches
- Build machine learning and deep learning models
- Communicate analytical findings to technical and non-technical stakeholders
- Drive feature consistency reliability reuse
- Engineer features from structured and unstructured data
- Establish attribute quality testing and monitoring
- Evaluate internal and external data sources
- Implement alerting for data and feature issues
- Lead risk attribute library design and governance
- Own attribute and model quality end to end
- Partner to prototype and productionize feature engineering
- Use large language model techniques on unstructured text
Perks/Benefits
- N/A
Skills/Tech-stack
Amazon Web Services | Anomaly Detection | Apache Spark | Clustering | Data Drift | Data Drift Detection | Data Quality | Data leakage | Data quality monitoring | Databricks | Decision Trees | Deep learning | Drift Detection | Feature Engineering | Generalized Linear Models | Gradient boosting | K-Nearest Neighbors | K-nearest | Language Model | Large Language Model | Linear Models | Machine Learning | Model Validation | Nearest neighbors | Python | Quality monitoring | Random Forests | Regression | Scala | Scenario Analysis | Simulation | Snowflake | Statistical Analysis | Statistical Analysis System | TensorFlow | Transformer | Web Services
Education
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