By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use . I further attest that all information I submit in my employment application is true to the best of my knowledge.
Job Description
Objective / Purpose:
Describe at the highest level the team where this job sits and how this role will contribute to the team’s delivery of critical function.
• Serve as a Senior Manager-level Clinical Data Scientist within Data & Quantitative Sciences, applying statistical, data science, and analytical methods to support clinical development programs.
• Partner with cross-functional study teams to deliver analysis-ready data, perform quantitative analyses, interpret results, and generate decision-support insights.
• Deliver fit-for-purpose statistical, data science, and advanced analytics activities for assigned studies and study-level workstreams.
• Collaborate with Clinical, Clinical Pharmacology, PSPV, Clinical Data Management, Translational Sciences, Regulatory, Clinical Operations, Statistical Programming, and external partners to support high-quality, traceable, analysis-ready, and submission-ready data.
• Apply modern clinical data science practices, including automation, reusable analytics workflows, and AI/ML-enabled approaches, while maintaining scientific rigor, regulatory awareness, and patient-focused decision making.
Accountabilities:
Primary duties and responsibilities; essential functions only.
• Execute clinical data science activities for assigned studies, ensuring timely delivery of high-quality analyses, data review, and quantitative insights that support study objectives.
• Perform exploratory analyses, data visualization, and quantitative assessments using clinical trial, biomarker, external, and real-world data sources.
• Collaborate with Clinical Data Management, Clinical Pharmacology, PSPV, Clinical Operations, and Translational Sciences to support study objectives and evidence generation.
• Translate scientific and clinical questions into analysis-ready datasets, specifications, and reproducible analytical workflows.
• Support integrated data review activities by identifying data trends, inconsistencies, and potential risks requiring further investigation.
• Apply established statistical, machine learning, simulation, and visualization methods to support interpretation of study results and development decisions.
• Contribute to the review of analysis outputs, visualizations, and technical documentation to ensure quality, traceability, and reproducibility of deliverables.
• Review and contribute to analysis outputs produced by internal teams and external partners, ensuring quality and adherence to established standards and processes.
• Identify and communicate risks related to data quality, analytical assumptions, timelines, and quantitative outputs to functional stakeholders.
• Contribute to continuous improvement efforts through automation, reusable code, standard methodologies, and adoption of approved technologies and workflows.
• Contribute to departmental standards, process improvements, and technology adoption initiatives as assigned.
• Share technical expertise and support onboarding and development of less experienced team member
Education & Competencies (Technical and Behavioral):
Essential and desirable education and competency requirements to perform the primary responsibilities of the job.
Education / Experience
• PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or related field with 5+ years of relevant experience; or MS with 7+ years of relevant experience. Equivalent combinations should be reviewed with HR.
• Experience supporting quantitative analyses and data science activities within pharmaceutical, biotechnology, healthcare research, or other…