Manager, Biostatistics

Responsibilities:

• Provide expert technical and strategic leadership in the design, analysis, and interpretation of complex clinical and real-world data studies, with a focus on high-impact projects.

• Collaborate cross-functionally with Engineering, Clinical/Medical, Data Science, and other stakeholders to drive project success and translate research into actionable business and clinical insights.

• Lead development on statistical analysis plans -sample size and power calculations, and propose accurate and efficient statistical methodologies 

• Oversee and independently execute statistical analyses for studies of high complexity, proactively identifying and addressing methodological challenges and improving or extending standard methods as needed.

• Provide statistical support required for any regulatory submissions 

• Independent work on complex problems, and selecting and adapting novel methods as appropriate

• Collaborate in an interdisciplinary role with scientists and engineers to translate research into actionable insights for our clients

• Stay current with advances in statistical methodologies, regulatory requirements, and industry best practices relevant to clinical trials and real-world data studies.

• Comply with all regulations and Company procedures

• Mentor and provide guidance to junior and senior biostatisticians, offering both high-level project leadership and detailed technical review (e.g., SAP review, code validation).

Required Experience:

• Ph.D. or Masters Degree in Biostatistics, Statistics, or a related field with 4+ years (Ph.D.) / 6+ years (MS/MA) relevant industry experience.

• Demonstrated expertise in advanced statistical analysis methods, experimental design, and survival analysis, with strong business domain knowledge in oncology, cardiology, and/or genomics

• Proven ability to improve or extend standard statistical design and analysis methods to address project-specific challenges

• Experience developing and reviewing statistical analysis plans (SAPs) and independently running analyses for complex studies with minimal oversight

• Proficiency in R and other relevant statistical software, with experience in code review and validation.

• Excellent communication, organizational, and problem-solving skills