Manager, Computational Biology (Early Oncology)

Role: Lead and mentor a team of data scientists and computational biologists focused on oncology drug discovery, integrating multi-omics datasets to identify novel therapeutic targets and validate disease mechanisms. Key responsibilities include designing and executing analyses for target nomination, developing biomarker and patient stratification strategies, and collaborating across teams to scale analytical tools. The role involves maintaining a hands-on contribution of 50% in complex data integration and analysis, and presenting findings to stakeholders. Qualifications: PhD in Computational Biology, Bioinformatics, or related field with 5+ years (PhD) or 7+ years (MS) industry experience in oncology or drug discovery; proven management experience; deep expertise in cancer biology, biomarker discovery, and multi-omics data analysis (phenomics, transcriptomics, proteomics). Technical skills in Python or R, data visualization, and familiarity with large oncology datasets (e.g., TCGA, DepMap) are required. Preferred: experience with high-throughput screening, clinical biomarker qualification, and familiarity with IND-enabling studies. High-value specifics include a focus on oncology, precision medicine, and early-stage therapeutic development. The position is hybrid, located in Salt Lake City or New York City, with at least 50% in-office work.