Senior Manager, Scientific AI Engineer

Key Responsibilities:

• Design, develop, and prototype AI/ML solutions addressing Oncology discovery, translational, and clinical development challenges.
• Apply advanced analytical and machine learning methods to multimodal datasets (e.g., molecular, clinical, real-world, literature).
• Own solutions end-to-end, from problem framing and data exploration through model development and user-facing outputs.
• Collaborate with domain experts to ensure solutions are scientifically grounded and decision relevant.
• Rapidly iterate on prototypes based on user feedback and evolving scientific needs.
• Contribute technical expertise to solution design discussions led by the Oncology AI Product & Engineering Lead.
• Document methods, assumptions, and limitations to support transparency and responsible AI practices.

• Bachelor’s degree + 6+ years OR Master’s + 5+ years OR PhD + 1+ year; advanced degree in computational biology, data science, machine learning, engineering, or related field strongly preferred.
• Demonstrated experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics environments.
• Strong hands-on programming skills (e.g., Python) and experience with data pipelines and ML frameworks.
• Solid understanding of Oncology biology, translational science, or clinical development workflows.
• Ability to operate independently in ambiguous problem spaces and deliver working prototypes.

• Experience in pharma, biotech, or AI-driven health technology startups.
• Familiarity with prototyping approaches for AI products rather than long-cycle production systems.
• Experience working with large, heterogeneous datasets common to Oncology R&D.