Qualifications

• PhD in statistics or biostatistics, or equivalent experience with a strong publication record.
• Experience developing statistical plans for clinical studies, especially in oncology.
• Strong problem-solving abilities and familiarity with data visualization and reproducible research.
• Proficiency in Python and R, with experience managing large biomedical datasets.
• Expertise in survival analysis, Bayesian methods, and causal inference.
• Knowledge of modern machine learning techniques.

Responsibilities

• Design and implement statistical evaluation plans for AI models.
• Write applications for data access from completed clinical trials.
• Evaluate AI models using data from completed clinical trials.
• Collaborate with a multidisciplinary team of engineers and scientists.
• Engage in research projects with academic and industry stakeholders.
• Contribute to regulatory submissions and documentation.
• Present findings to both technical and non-technical stakeholders.
• Mentor junior biostatisticians and data scientists.

Benefits

• Opportunity to lead innovative research projects in AI and biostatistics.
• Collaboration with leading experts in a multidisciplinary environment.
• Mentorship opportunities for personal and professional growth.
• Access to cutting-edge data in oncology for impactful research.
• Engagement in high-profile regulatory submissions and publications.