Principal Scientist, Translational Informatics and Predictive Sciences
Core
Apply bioinformatics, statistical, and computational biology approaches to analyze large-scale clinical and real-world datasets to discover biomarkers and inform development strategies for solid tumor oncology medicines.
Role type
Principal Scientist, Translational Informatics and Predictive Sciences
Builds
Data-driven insights for next-generation oncology medicines
Domain
Biopharma, Oncology, Computational Biology, Machine Learning
Deliverable
production ML models
Required skills
High-throughput molecular data analysis, R, Python, AI/ML methods, Statistical modeling, Multi-omics integration, Biomarker discovery
Preferred skills
Spatial omics, Oncology domain expertise, Drug development experience
Technologies
Next-generation sequencing, Single-cell technologies, Proteomics, Agentic AI coding tools
Responsibilities
Partner with clinical and preclinical teams to design computational strategies for translational studies; Analyze high-dimensional molecular datasets to generate mechanistic insights; Apply and develop ML/AI methods for predictive modeling and data integration; Provide scientific leadership and mentorship on analytical best practices; Communicate scientific results to decision-making bodies to influence cross-functional strategy
Seniority
Principal, hands-on IC with strategic impact
