Senior Applied Scientist, Credit Risk
Tasks
- Apply machine learning statistics causal inference optimization and economics
- Build backtesting and validation frameworks
- Collaborate with business product data and engineering stakeholders
- Deploy models in production
- Design machine learning models for credit risk decisioning
- Develop features and prototypes
- Evaluate structured and unstructured data sources
- Generate and communicate data driven insights
- Integrate new data sources into models
- Monitor model performance and drift
- Optimize credit risk models
- Own applied science development lifecycle
- Write documentation and test models for reliability
Perks/Benefits
- 401k employer match
- Flexible PTO
- Health and wellness stipend
- Home office & equipment stipend
- Intra office travel budget
- Medical, dental, and vision insurance
- Parental leave
- Weekly coffee stipend
Skills/Tech-stack
Backtesting | Causal Inference | Data Analysis | Data Exploration | Economics | Exploratory Data Analysis | Feature Engineering | Machine Learning | Model Monitoring | Model Validation | NumPy | Optimization | Pandas | Predictive Modeling | Production Machine Learning | PyTorch | Python | SQL | Scikit-learn | Statistics
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
Cities
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