Senior Research Statistician (Hybrid)

Responsibilities

• Work closely with study statisticians, programmers, and cross-functional stakeholders to assess study progress, identify emerging trends and risks, and provide analytical support that enhances trial oversight while maintaining scientific rigor.
• Contribute to design, analysis and reporting of clinical trials or other scientific research studies.
• Aid in the development of protocols and/or statistical analysis plans with details for programming implementation.
• Implement sound statistical methodology in scientific investigations.
• Identify scientifically appropriate data collection instruments.
• Identify and report data issues or violations of study assumptions.
• Provide programming specifications for derived variables and analysis datasets.
• Collaborate with Data Science in preparing for database lock.
• Perform statistical analyses as per the analysis plan with supervision.
• Collaborate with Statistical Programming to ensure the delivery of high-quality outputs according to agreed-upon timelines.
• Evaluate appropriateness of available software for planned analyses and assess needs for potential development of novel statistical methodology.
• Develop strategy for data presentation and inference.
• Ensure appropriate interpretation of statistical deliverables in collaboration with other functions.
• Collaborate in publication of scientific research.
• Ensure accuracy and internal consistency of reports and publications, including tables, listings, and figures.
• Ensure the accuracy of the statistical component of scientific reports and/or publications with high quality.
• Support communications between assigned product team(s) and functional management.
• Build/drive cross-functional relationships and collaboration.

Qualifications

• PhD in Statistics, Biostatistics, Data Science, Mathematics, Epidemiology, or a related quantitative field.
• Strong understanding of statistical methodologies and clinical trial data analysis.
• Experience with statistical programming in R.
• Experience analyzing complex datasets and translating findings into actionable insights.
• Ability to conduct exploratory analyses, interim analyses, and data monitoring activities.
• Strong problem-solving and quantitative reasoning skills.
• Excellent written and verbal communication skills.