Associate Director, Data Science, Computational Oncology
Core
Lead computational oncology research by analyzing multi-omics and functional genomics datasets to understand cancer biology, nominate drug targets, and prioritize drug combinations.
Role type
Associate Director, Data Science (Computational Oncology)
Builds
Target nomination and biomarker discovery for oncology and immunology programs
Domain
Biopharmaceuticals / Computational Oncology / Genomics
Deliverable
production ML models | research
Required skills
Cancer genomics, Multi-omics analysis, Functional genomics screens, Machine learning, Deep learning, Statistical modeling, Network-based analysis, R, Python, Linux, Cloud platforms (AWS, Databricks)
Preferred skills
Foundation models for single-cell data, Agentic AI/LLMs, CRISPR screen analysis, Gene regulatory network analysis
Technologies
AWS S3, Nextflow, Databricks, Posit, Git, TCGA, GTEx, CCLE, CPTAC, DepMap
Responsibilities
Analyze large-scale NGS datasets (bulk RNA-seq, WES/WGS, scRNA-seq) to understand disease mechanisms; Interpret functional genomics and perturbational screens (CRISPR, Perturb-seq) to establish target dependency; Nominate and prioritize drug combinations using expression profiling and biological evidence; Apply deep learning and single-cell foundation models for cell-type deconvolution and patient stratification; Use LLM-based agents to accelerate evidence synthesis; Collaborate with experimental scientists and software engineers to ensure reproducible research.
Seniority
Associate Director, hands-on IC with leadership responsibilities