Associate Director, Data Science

Role: Senior scientific and technical leader in drug development data science within BMS's DSAA team, driving strategy and execution to support early-to-late phase clinical programs. Responsibilities: provide strategic guidance on multi-modal data analysis including genomics, proteomics, imaging, and biomarker data; lead development of innovative statistical, AI/ML, and computational methods; oversee data integration, modeling, and visualization; define standards for reproducible pipelines; mentor junior scientists; and collaborate with cross-functional teams such as Biostatistics, Translational, and Clinical Sciences. Qualifications: Ph.D. in a quantitative field (e.g., Computational Biology, Biostatistics) with >6 years industry experience or Master’s with >8 years; proven expertise in data science, statistical modeling, AI/ML, and clinical trial data analysis; proficiency in Python, R, SQL, and cloud platforms; deep understanding of drug development, biomarkers, and regulatory considerations. Preferred: experience with genomics, proteomics, imaging, NLP, survival analysis, causal ML, and real-world data sources; knowledge of molecular biology and disease pathways; prior leadership or team management experience. HighValue: support for therapies in clinical development, utilization of advanced analytics to influence drug programs, cross-disciplinary collaboration, and work in a hybrid or onsite setting with some travel.