Applied ML Scientist, Clinical Risk Modelling
Tasks
- Build retrospective patient cohorts
- Collaborate with software engineers for production integration
- Create clinically interpretable risk tiers
- Develop prognostic machine learning models
- Document datasets modelling decisions and validation results
- Engineer time windowed features
- Evaluate discrimination calibration and subgroup performance
- Prevent temporal data leakage
- Validate predictive models
Perks/Benefits
- Fitness program
- Flexible schedule
- Health insurance for dependents
- Learning opportunities
- Nutritionist Consultation
- Reimbursable home office allowance
- Wellness program
- Work from home
Skills/Tech-stack
Clinical prediction | Data Leakage Prevention | Data leakage | Electronic Health Records | Event modeling | Feature Engineering | GDPR | Gradient boosting | HIPAA | Health Records | Leakage prevention | Model Validation | Model calibration | NumPy | Pandas | Python | Regularized regression | Scikit-learn | Survival analysis | Time to Event | Time-to-event modeling
Education
N/A
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