Principal Data Scientist (AI-assisted Clinical Development)
Tasks
- Architect machine learning and generative AI systems
- Conduct exploratory data analysis
- Create software requirements for model productization
- Design simulation studies for trial designs
- Develop machine learning methods for clinical development
- Develop reproducible data pipelines
- Integrate models into user applications
- Lead cross functional data science efforts
- Optimize model performance and mitigate bias
- Provide best practice guidance for statistical modeling
- Publish and present scientific methodologies
- Train evaluate and deploy machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
Adversarial Networks | Algorithmic Fairness | BRMS | Bayesian Methods | Bias detection | Causal Inference | Compliance | Concept drift | Data Processing | Data Processing Pipelines | Decision Theory | Dimensional data | Explainability | Generative AI | Generative Adversarial Networks | High Dimensional Data | Machine Learning | Model Deployment | Model Evaluation | Model Training | Probabilistic Programming | Processing pipelines | PyTorch | Pymc | Python | R | Scikit-learn | Simulation studies | Stan | Statistical modeling | TensorFlow | Traceability
Education
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
Regions
Countries
States
Cities
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