Senior Manager, Scientific AI Engineer

Role: Scientific AI Engineer focused on designing and implementing AI/ML solutions to support Oncology R&D decision-making. Responsibilities include developing end-to-end AI solutions addressing discovery, translational, and clinical challenges; applying advanced analytics to multimodal datasets (molecular, clinical, real-world); collaborating with Oncology scientists to ensure scientific rigor and decision relevance; and iterating prototypes based on feedback. Qualifications: Bachelor's degree with 6+ years, Master’s with 5+ years, or PhD with 1+ year in computational biology, data science, or related fields; strong programming skills (Python); experience in applied AI/ML within life sciences or healthcare; and understanding of Oncology biology and clinical workflows. Preferred: pharma or biotech experience, familiarity with heterogeneous Oncology datasets, and AI prototyping approaches. High-Value: Oncology, translational science, clinical development, multimodal datasets, applied AI/ML, and cross-functional collaboration. Work setup and travel details are not specified.