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Job Description

About the role:

You will serve as a Senior Manager-level Clinical Data Scientist within Data and Quantitative Sciences, applying statistical, data science, and analytical methods to support clinical development programs. You will partner with cross-functional study teams to deliver analysis-ready data, quantitative analyses, interpretation of results, and decision-support insights.

You will also help advance modern clinical data science practices through automation, reusable analytics workflows, and artificial intelligence and machine learning enabled approaches, while keeping scientific rigor, regulatory awareness, and patient-focused decision making at the center of your work.

How you will contribute:

• Perform exploratory analyses, data visualizations, and quantitative assessments using clinical trial, biomarker, external, and real-world data sources.
• Apply statistical, machine learning, simulation, and visualization methods to help interpret study results and inform development decisions.
• Translate scientific and clinical questions into analysis-ready datasets, specifications, and reproducible analytical workflows.
• Deliver clinical data science activities for assigned studies, including timely analyses, data review, and quantitative insights that support study objectives.
• Support integrated data review by identifying data trends, inconsistencies, and potential risks that need further review.
• Review analysis outputs, visualizations, and technical documentation to help ensure quality, traceability, and reproducibility.
• Review and contribute to analysis outputs produced by internal teams and external partners, ensuring quality and alignment with established standards and processes.
• Identify and communicate risks related to data quality, analytical assumptions, timelines, and quantitative outputs to functional partners.
• Collaborate with Clinical Data Management, Clinical Pharmacology, PSPV, Clinical Operations, and Translational Sciences to support study objectives and evidence generation.
• Share technical expertise and support onboarding and development of less experienced team members.
• Contribute to departmental standards, process improvements, and technology adoption initiatives as assigned.
• Support continuous improvement through automation, reusable code, standard methods, and adoption of approved technologies and workflows.

Minimum Requirements/Qualifications:

• PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or a related field with 3 or more years of relevant experience; or a master’s degree with 6 or more years of relevant experience. Equivalent combinations should be reviewed with Human Resources.
• Experience supporting quantitative analyses and data science activities within pharmaceutical, biotechnology, healthcare research, or other regulated clinical development environments.
• Demonstrated ability to contribute to clinical development decisions through quantitative analysis, data interpretation, and clear communication of evidence.
• Experience working on cross-functional study teams and collaborating across disciplines to achieve study objectives.
• Experience working with clinical trial data and at least one additional data type such as biomarker, real-world, external, imaging, digital health, or other high-dimensional data sources.
• Strong knowledge of clinical trial design, drug development, endpoints, estimands, biomarkers, data interpretation, and the role of analytics in clinical decision making.
• Strong foundation in statistics and quantitative methods, including longitudinal analysis, survival methods, causal reasoning, simulation, predictive modeling, and communication of uncertainty.
• Hands-on proficiency in R and or Python, with working knowledge of SAS and SQL, and the ability to support reproducible analyses, code quality, version control, and validated workflows.
• Working knowledge of Clinical Data Interchange Standards Consortium standards, including Study Data Tabulation Model, Analysis …