Principal Scientist, Predictive Modeling and Applied AI (Clinical Development)
Tasks
- Apply machine learning deep learning and causal inference for applied AI in RWD RWE
- Author abstracts manuscripts and external publications
- Develop digital twins and patient-level simulation models
- Develop training on predictive models for cross functional partners
- Lead design development validation of predictive modeling solutions
- Partner with Product Engineering and Data teams to build scalable predictive analytics platforms
- Provide scientific leadership for client engagements
- Represent company at conferences and publish scientific work
- Select model designs for validity interpretability and clinical decision use
- Translate complex methods into decision relevant insights
Perks/Benefits
Skills/Tech-stack
Causal Inference | Claims data | Clinical Research | Clinical Trial Design | Clinical research data | Clinical research data management | Clinical trial | Clinical trial analysis | Data Governance | Data Management | Deep learning | Digital Twins | EHR | Event modeling | Gradient boosting | Longitudinal data | Machine Learning | Multimodal modeling | Neural Networks | Predictive Modeling | Python | R | RWD | RWE | Research data management | Time to Event | Time-to-event modeling | Trial Analysis | Trial design | XGBoost
Education
Roles
Data Scientist | Principal | Principal Scientist | Scientist
Regions
Countries
States
Cities
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