Applied AI Head

About the role

Roche Information Solutions China is looking for an Applied AI Head to report to the Head of RIS China and join the RIS China leadership team. You will lead a high-performing team driving digital research and innovation, especially around AI, and influence cross-functional teams. The role sits within the broader mission of preventing, stopping and curing diseases and ensuring access to healthcare.

Key responsibilities

• Define the vision, strategy and roadmaps for AI-driven innovation, shaping new products, services and business models.
• Lead a team of Applied Scientists who turn concepts and business hypotheses into prototypes, validating viability, desirability and feasibility.
• Focus on early-stage understanding and exploration, using rapid prototyping and customer insights.
• Implement observability and reliability for AI models, monitoring performance, bias and data/model drift.
• Champion responsible AI, ethics, governance, IP and security, and manage AI-related risks.
• Work with the product lifecycle and engineering teams to reuse, consolidate and simplify technology, building on the China Digital Platform and common infrastructure.
• Analyze the digital healthcare market, competitors and technology trends, and co-innovate with internal and external partners.
• Build, lead and mentor a multidisciplinary team of applied scientists and innovation professionals.

Required profile

• Master's or Ph.D. in medicine, computer science, data science, artificial intelligence, biomedical engineering or a related health science field.
• 10+ years of hands-on experience applying machine learning, deep learning or statistical modeling to complex clinical or life science problems.
• Proven track record of moving AI/ML from lab proof-of-concept to real-world validation.
• Leadership experience, including leading digital product management teams; previous experience in digital healthcare is highly desired.
• Fluent in spoken and written English and Mandarin.

Required skills

• Foundational knowledge of quantitative methods (mathematical modeling, machine learning) and clinical/scientific principles.
• Hands-on experience with PyTorch, TensorFlow and languages such as Python, R, Java or JavaScript.
• Familiarity with UX, APIs, microservices, analytics, XaaS and generative AI concepts (RAG, AI agents).
• Experience with healthcare data such as EHR/EMR, medical imaging, digital pathology and multi-modal data; familiarity with HL7, FHIR, OMOP, LIS and EMR is highly preferred.
• Design thinking, prototyping and agile methodology.