Associate Principal Scientist, Data Science (Virtual Screening & Receptor Biology)

We are seeking a seasoned data scientist to direct a virtual receptor screening team within our Data Science Ingredient Modeling unit, collaborating with chemists and biologists to leverage protein and molecular AI in receptor biology.

Key Responsibilities

• Implement machine learning and protein AI models for receptor-ligand interactions using structural biology expertise
• Conduct in silico screening, docking analyses, and energy calculations
• Lead adoption of computational best practices across the global scientific community
• Build and scientifically direct a dedicated data science team
• Stay current with advances in computational biology and protein AI
• Apply modern software development practices and Python proficiency
• Develop ML/AI models predicting formulation performance across diverse applications
• Support product development with data science models and pipelines
• Translate research findings into practical applications

Requirements

• Ph.D. in Receptor Biology, Structural Biology, Computer Science, AI, or related field
• 5-10 years of academic or industrial experience in ingredients or small molecule discovery
• Demonstrated expertise in computational structural biology, virtual docking, and molecular dynamics
• Deep understanding of structural and receptor biology, particularly chemosensory receptors (GPCRs, ion channels)
• Advanced proficiency in ML, Python, code management, and CI/CD pipelines
• Leadership experience in R&D projects and team mentoring
• Strong problem-solving and collaborative communication skills