Senior Data Scientist, Computational Biology
Core
Design, implement, and advance AI-driven frameworks and analytical models to enable translational insights from clinical trial data, linking molecular and clinical phenotypes to disease stratification and outcomes.
Role type
Senior IC computational biology data scientist (clinical development)
Builds
Production-grade predictive and prognostic biomarker models, multi-omic integration frameworks, and AI-enabled analytical systems for drug development
Domain
Biopharmaceuticals / Clinical Development / Computational Biology
Deliverable
production ML models
Required skills
Multi-omic data integration, predictive and prognostic biomarker modeling, advanced statistical methodologies (longitudinal, mixed-effects, survival analysis), causal inference, deep learning, foundation model application, Python, R, PyTorch, TensorFlow, scikit-learn, tidymodels, clinical trial data analysis, NGS, transcriptomics, proteomics, imaging data processing
Preferred skills
Peer-reviewed publications in reputable journals, open-source contributions (GitHub), experience with agentic AI systems, prior experience in large global biotech or pharmaceutical organizations
Technologies
PyTorch, TensorFlow, scikit-learn, tidymodels, GPT-class models, factor models, MOFA, graph-based methods
Responsibilities
Design and implement predictive biomarker models using clinical trial data; develop multi-omic integration frameworks; apply advanced statistical methodologies for clinical development; build and evaluate ML/DL and causal inference models; partner with engineering teams to ensure reproducibility and scalability; translate biological questions into analytical strategies; collaborate with biomarker scientists, clinicians, and data engineers
Seniority
Senior, hands-on IC
