Head Of Data Science & Credit Risk
Tasks
- Apply causal inference for experimentation
- Build and scale external data partnerships
- Build early warning systems
- Build real time decisioning pipelines
- Define data science and credit risk strategy
- Design and deploy fraud detection models
- Design and deploy machine learning credit scoring models
- Develop credit risk policies and approval strategies
- Develop expected credit loss modeling
- Drive experimentation with A/B testing
- Establish MLOps standards for model deployment and monitoring
- Lead portfolio risk analytics and stress testing
- Lead underwriting models and decisioning systems
- Partner to optimize unit economics and provisioning
- Recruit and mentor data science and risk teams
- Translate analytics into executive insights
Perks/Benefits
- Access to modern ML stack
- Career progression opportunities
- Equity participation
- Fast paced mission driven environment
- Strong ownership and autonomy
Skills/Tech-stack
A/B | A/B Testing | Alternative data | B testing | BigQuery | Causal Inference | Credit Bureaus | Credit Scoring | Data Pipelines | Expected Credit Loss | Fraud Detection | GCP | MLOps | MLflow | Machine Learning | Model Monitoring | Portfolio Risk | Portfolio risk analytics | Real Time | Real-time Processing | Risk Analytics | SQL | Stress Testing | Time processing | Underwriting | Version control
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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