Tech Stack

Description

You will lead statistical design, analysis, and interpretation for exploratory data analyses and real-world evidence studies in oncology. Collaborate with cross-functional teams to deliver data-driven insights supporting scientific understanding and evidence generation.

Requirements

• Ph.D. or M.S. in Statistics/Biostatistics with 5+ years (PhD) or 8+ years (MS) biotech/pharma experience
• Solid knowledge of oncology statistical methodologies including survival analysis and causal inference
• Hands-on experience in exploratory analysis of oncology trials
• Proficiency in SAS and/or R
• Strong verbal and written communication skills

Responsibilities

• Lead statistical design, analysis, and interpretation for exploratory data analyses using clinical trial data, real world data, and HEOR studies
• Partner with cross-functional teams including clinical development, medical affairs, and regulatory to execute evidence generation plans
• Apply statistical methodologies like survival analysis, machine learning, and causal inference to oncology questions
• Contribute to analysis plans, technical specifications, and interpretation of results
• Review statistical deliverables from internal programmers or external vendors