The Opportunity:
As a Principal Statistical Methodology Data Scientist you will:
- You serve as a methodological thought partner to study teams, providing expert guidance on complex design and analysis across programs
- You lead the development and institutionalization of methodologies that improve decision-making at trial and portfolio levels (e.g., quantitative go/no-go criteria, simulation frameworks, model-based projections)
- You shape cross-functional understanding of innovative statistical methods through consultation, publications, and leadership of education efforts
- You anticipate regulatory trends and industry shifts, integrating relevant methodologies into internal practices and guiding external engagements
- You act as a connector across teams, surfacing recurring challenges and co-creating scalable solutions to elevate analytical excellence in the organization
- You drive external collaboration through active participation in consortia, joint working groups, or regulatory-facing initiatives
- You mentor junior staff and influence the strategic direction of Statistical Methodology through thought leadership, vision-setting, and capability building
Who you are:
- You hold a PhD in Biostatistics, Statistics, Data Science, Computer Science, or a related quantitative discipline
- You have 6+ years of experience designing and applying advanced analytics to complex biomedical data in clinical trial research
- You bring deep expertise in statistical computing and advanced modeling, with a track record of developing novel or custom analytical solutions
- You are recognized as a technical expert and thought partner within the organization or broader field
- You have experience mentoring others and contributing to internal standards, strategy, or capability development
- You show respect for cultural differences when interacting with colleagues in the global workplace
Preferred:
- Experience developing novel or fit-for-purpose analytical methods for different types of datasets
- Demonstrated leadership in designing scalable workflows or frameworks adopted across multiple projects or teams
- Track record of influencing portfolio- or program-level decisions through rigorous analytical insights
- Publications, presentations, or internal white papers that showcase innovative analytical thinking
- Thought leadership in emerging data science areas relevant to pharmaceutical development (e.g., AI/ML in translational research, real-world data integration, predictive biomarkers)
The expected salary range for this position based on the primary location of California is $185,200 - $343,900. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Relocations Benefits are not available for this job posting.
Benefits
#PDD
The Position
The Statistical Methodology Data Scientists play a strategic role in enabling the adoption of fit-for-purpose statistical methodologies to drive scientific rigor and decision-making excellence. This team serves as a center of excellence focused on consultation, education, and outreach to ensure that innovative and appropriate methods are applied across programs and portfolios.
Statistical Methodology Data Scientists collaborate closely with project teams, biostatisticians, and cross-functional stakeholders to identify methodological needs, prototype solutions (e.g., estimand frameworks, trial simulations, covariate adjustment strategies), and support scalable adoption through training, templates, and open source software/tools. They engage in portfolio-level analyses, scenario modeling, and quantitative frameworks that inform go/no-go decisions and optimize clinical strategy.
The team also maintains key external relationships, representing the company in consortia, scientific working groups, and regulatory collaborations to stay at the forefront of methodological advances in the pharmaceutical industry.