Job Description
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Company Overview
A leading global pharmaceutical organization is seeking an experienced statistical methodology professional to strengthen the application of innovative, fit-for-purpose statistical methodologies across clinical development programs and portfolios. The organization focuses on applying rigorous scientific and quantitative approaches to improve decision-making, clinical strategy, and the development of innovative therapies.
The Statistical Methodology Data Science team serves as a center of excellence focused on consultation, education, and methodological outreach. The team works closely with study teams, biostatisticians, and cross-functional stakeholders to identify methodological needs, develop innovative analytical solutions, and establish scalable approaches that improve analytical excellence across the organization.
The Opportunity
As a Principal Statistical Methodology Data Scientist, the professional will:
- Serve as a methodological thought partner to study teams, providing expert guidance on complex study design and statistical analysis across programs.
- Lead the development and institutionalization of methodologies that improve decision-making at both trial and portfolio levels.
- Develop quantitative go/no-go criteria, simulation frameworks, model-based projections, and other advanced analytical approaches.
- Shape cross-functional understanding of innovative statistical methods through consultation, publications, training, and educational initiatives.
- Anticipate regulatory trends and industry developments and integrate relevant methodologies into internal practices.
- Guide external engagements related to emerging statistical methodologies and pharmaceutical development.
- Identify recurring analytical challenges across teams and co-create scalable solutions to elevate organizational analytical capabilities.
- Drive external collaboration through participation in industry consortia, scientific working groups, and regulatory-facing initiatives.
- Mentor junior professionals and contribute to the strategic direction of Statistical Methodology through thought leadership, vision-setting, and capability development.
- Support the adoption of innovative statistical methods through training, templates, open-source software, and analytical tools.
- Contribute to portfolio-level analyses and quantitative frameworks that inform strategic clinical development decisions.
Required Qualifications
- PhD in Biostatistics, Statistics, Data Science, Computer Science, or a related quantitative discipline.
- 6+ years of experience designing and applying advanced analytics to complex biomedical data within clinical trial research.
- Deep expertise in statistical computing and advanced statistical modeling.
- Demonstrated experience developing novel or customized analytical solutions.
- Recognition as a technical expert and strategic thought partner within an organization or the broader scientific field.
- Experience mentoring professionals and contributing to internal standards, strategy, or capability development.
- Strong ability to collaborate with cross-functional teams and stakeholders.
- Demonstrated respect for cultural differences and the ability to work effectively within a global workplace.
Preferred Qualifications
- Experience developing novel or fit-for-purpose analytical methodologies for different types of datasets.
- Demonstrated leadership in designing scalable workflows or analytical frameworks adopted across multiple projects or teams.
- Proven ability to influence portfolio- or program-level decisions through rigorous analytical insights.
- Publications, presentations, or internal white papers demonstrating innovative analytical thinking.
- Thought leadership in emerging data science areas relevant to pharmaceutical development.
- Experience with AI and machine learning applications in translational research.
- Knowledge of real-world data integration and advanced predictive analytics.
- Experience developing predictive biomarkers or other innovative quantitative approaches.
- Strong communication and educational skills for explaining advanced statistical methodologies to diverse audiences.
Disclaimer
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