Associate Director, Data Science, Computational Oncology

Role: Associate Director of Data Science in Computational Oncology, focusing on analyzing complex multi-omics datasets to understand cancer biology and support target and biomarker discovery. Responsibilities: perform large-scale data analysis (RNA-seq, WES/WGS, scRNA-seq), interpret functional genomics screens (CRISPR, Perturb-seq), prioritize drug combinations, and apply advanced statistical, network, machine learning, and deep learning methods, including AI and foundation models. Collaborate with multidisciplinary teams to translate data into actionable insights across oncology and immunology projects. Qualifications: PhD in computational biology, bioinformatics, biostatistics, genetics, or related STEM field with 4+ years (or MS with 8+ years, BS with 12+ years) of relevant experience; extensive experience analyzing NGS data, strong programming skills (R, Python), familiarity with cloud platforms (AWS, Databricks), and knowledge of major cancer genomics resources. Preferred: post-doctoral or industry experience in cancer genomics or computational oncology, expertise with functional genomics screens, foundation models, and gene regulatory network analysis. HighValue: oncology, cancer genomics, multi-omics, single-cell and functional genomics datasets, AI/ML applications, target nomination, biomarker discovery, early-stage research (preclinical), hybrid work setup in Boston, MA, with up to 10% travel.