Early Development Biometrics Lead

About the role

Roche is looking for an Early Development Biometrics Lead in Shanghai to lead the Early Development Biometrics team in PDD China, operating within the China Early Development Center of Excellence (CED CoE). The role leads an integrated, multidisciplinary team of Biostatisticians, ADS Programmers and Data Managers and acts as the primary strategic partner to cross-functional leaders in the CED CoE.

Key responsibilities

• Contribute to and influence the China strategy in global early clinical development plans
• Provide scientific and data science leadership across the China early development portfolio so trials are scientifically rigorous and data-ready
• Oversee a strategy combining statistical design, modern data acquisition and FAIRification, and advanced programming workflows
• Guide the use of Bayesian methods, simulation and adaptive designs to support early decision-making under uncertainty
• Promote advanced analytics, automated pipelines and modern data science capabilities
• Partner with global EDB leadership to integrate global strategy, methodology and standards locally
• Drive technical and operational excellence in Biostatistics, ADS Programming and Data Management
• Lead, mentor and develop the team, and oversee capacity planning, workload balancing and capability scaling

Required profile

• PhD or Master's degree in Biostatistics, Statistics, Data Science, Computer Science or a related quantitative discipline
• 12+ years of experience in clinical research or pharmaceutical development, including early development
• 3+ years of leadership experience (people, project or program)
• Proven statistical or biometrics leadership across multiple studies and programs
• In-depth knowledge of early phase clinical development, including scientific, technical and regulatory requirements
• Excellent communication skills and intercultural awareness

Preferred

• Experience leading statistical or data science contributions to early development strategies (dose finding, proof-of-concept, translational study design)
• Exposure to biomarkers, omics, imaging or real-world data
• Interest in or experience with digital innovation, AI/ML or advanced data science methods
• Ability to lead through ambiguity in a matrixed or agile environment