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).
Requirements
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.