Senior Applied Scientist, Credit Risk
Tasks
- Apply machine learning statistics causal inference optimization and economics methods to solve business problems
- Contribute to best practices for model development experimentation documentation testing and production reliability
- Design build and optimize machine learning models for credit risk decisioning and portfolio management
- Develop backtesting validation and monitoring frameworks for model performance and business impact
- Generate and communicate data driven insights to influence product risk and company strategy
- Investigate and integrate new structured and unstructured data sources into credit models
- Own applied science development lifecycle from data exploration to deployment monitoring and iteration
- Partner with product business engineering and data stakeholders to translate ambiguous problems into objectives
Perks/Benefits
- 401k employer match
- Budget for Intra Office Travel
- Centralized Home Office Equipment Ordering
- Centralized medical dental and vision insurance
- Flexible PTO
- Health and wellness stipend
- Parental leave
- Relocation support
- Unlimited AI token usage
- Weekly coffee stipend
Skills/Tech-stack
Backtesting | Causal Inference | Data Analysis | Data Exploration | Economics | Exploratory Data Analysis | Feature Engineering | Machine Learning | Model Monitoring | NumPy | Optimization | Pandas | Predictive Modeling | PyTorch | Python | SQL | Scikit-learn | Statistics | Structural modeling
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
Cities
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