Head Of Data Science & Credit Risk
Tasks
- Allocate capital based on risk
- Apply causal inference methods
- Build customer segmentation models
- Build early warning systems
- Conduct portfolio stress testing
- Create real time decisioning pipelines
- Define data science and credit risk strategy
- Deploy fraud detection models
- Design credit scoring models
- Develop underwriting models
- Establish risk thresholds
- Implement MLOps standards
- Lead technical teams and mentorship
- Manage provisioning strategies
- Model expected credit loss
- Monitor model performance in production
- Optimize Unit Economics
- Optimize customer value models
- Run experimentation with A B testing
- Set credit risk policies and approval strategies
Perks/Benefits
- Autonomy
- Career progression
- Equity participation
- Experimentation focused culture
- Modern ML stack access
- Ownership culture
Skills/Tech-stack
A/B | A/B Testing | B testing | BigQuery | Causal Inference | Credit Risk | Credit Scoring | Expected Credit Loss | Fraud Detection | GCP | MLOps | MLflow | Machine Learning | SQL | Statistical modeling | Stress Testing
Education
N/A
Roles
Data Science | Head | Head of Credit | Head of Credit Risk | Head of Data | Head of Data Science
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