Senior Manager, Oncology Early Stage Clinical Scientist
Pfizer
Google Cloud Platform
Salary
💰 $140,000 - $180,000 per year
Job Level
Senior
About the role
- Provide statistical leadership across Artera’s research and development pipeline and product lifecycle — spanning data acquisition, study design, model and product validation, regulatory and reimbursement submissions, and post-market evidence generation.
- Collaborate with R&D teams on model development strategies, providing statistical expertise on study design, validation approaches, and other key considerations that ensure scientific rigor and product credibility.
- Lead the application of rigorous statistical methodology, ensuring robustness, reproducibility, and high-quality evidence to support product development and research initiatives.
- Guide the development and review of statistical content for protocols, analysis plans, study reports, regulatory submissions, and peer-reviewed publications.
- Drive data governance, validation, and documentation practices that ensure compliance and support regulatory, reimbursement, and external stakeholder requirements.
- Represent Biostatistics as a scientific leader in cross-functional and external collaborations, communicating complex statistical concepts to diverse scientific, clinical, and business audiences.
Requirements
- Master’s degree or higher in Biostatistics, Statistics, or a related quantitative field.
- Strong working knowledge of statistical methods for clinical studies (e.g., clinical trials, validation studies).
- Skilled in R for statistical programming, simulation, and reproducible research workflows.
- Minimum 5 years of experience as a biostatistician, or equivalent combination of education and experience; experience as an industry biostatistician in biomarker, medical device, or biotech/biopharma preferred.
- Experience drafting and reviewing statistical sections of clinical study protocols, analysis plans, and regulatory documents.
- Demonstrated ability to communicate statistical concepts effectively to non-statistical audiences.
- (Nice-to-Haves) Familiarity with AI and machine learning methods, particularly in predictive and prognostic model development and validation.
- (Nice-to-Haves) Strong publication record and experience contributing to peer-reviewed manuscripts and conference presentations.
- (Nice-to-Haves) Knowledge and hands-on experience with regulatory submissions.
- (Nice-to-Haves) Experience supporting reimbursement/evidence generation submissions for payer decision-making.
