Head Of Data Science & Credit Risk
Tasks
- Analyze portfolio risk metrics
- Build real time decisioning pipelines
- Build underwriting models
- Create early warning systems
- Create segmentation models
- Define data science and credit risk strategy
- Deploy fraud detection models
- Design credit scoring models
- Develop credit risk policies
- Develop real time monitoring pipelines
- Establish MLOps standards
- Lead causal inference experiments
- Model expected credit losses
- Monitor model performance in production
- Optimize customer value predictions
- Optimize provisioning strategies
- Partner with external data providers and credit bureaus
- Recruit and mentor data science team
- Run A/B testing
- Run portfolio stress testing
- Set approval strategies
- Set risk thresholds
- Support capital allocation decisions
- Translate analytics into executive insights
Perks/Benefits
- Access to modern ML stack
- Career progression
- Contribution to Financial Inclusion
- Equity participation
- Fast paced mission driven environment
- Ownership and autonomy
Skills/Tech-stack
A/B | A/B Testing | B testing | BigQuery | Causal Inference | Cloud platform | Credit Risk | Credit Scoring | Customer Value | Customer Value Optimization | Data Pipelines | Expected Credit Loss | Fraud Detection | GCP | Google Cloud | Google Cloud Platform | MLOps | MLflow | Machine Learning | Portfolio Risk | Portfolio risk analytics | Real Time | Real-time Decisioning | Risk Analytics | SQL | Stress Testing | Underwriting | Value optimization
Education
N/A
Roles
Data Science | Data Science Manager | Head | Head of Credit | Head of Credit Risk | Head of Data | Head of Data Science | Manager
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