Director, Clinical Data Scientist - Statistics

• PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or a related field with 8+ years of relevant experience; or a master’s degree with 12+ years of relevant experience.

• Extensive experience in clinical development within the pharmaceutical, biotechnology, or healthcare research environment, with demonstrated ability to influence cross-functional decisions at study, asset, portfolio, or function level.

• Demonstrated experience contributing to regulatory submissions, health authority interactions, inspection readiness, and submission-oriented analysis, documentation, traceability, and response activities across multiple regulatory agencies or global health authorities.

• Demonstrated experience as a people manager or formal team leader, including coaching, performance input, talent development, workload prioritization, and support for employee engagement and growth.

• Experience providing technical leadership, matrix leadership, vendor oversight, and mentorship across cross-functional, geographically distributed, or externally supported delivery models.

• Track record of advancing analytical strategy, standards, automation, artificial intelligence and machine learning-enabled approaches, or modern data science practices in a regulated clinical development and submission environment.

• Expert knowledge of clinical trial design, drug development, endpoints, estimands, biomarkers, data interpretation, and the role of analytics in clinical decision making, regulatory strategy, and submission support.

• Strong foundation in statistics and quantitative methods, including longitudinal analysis, survival methods, causal reasoning, simulation, predictive modeling, and uncertainty communication for scientific, governance, and health authority audiences.

• Experience integrating and interpreting diverse data sources, including clinical trial, biomarker, real-world, external, imaging, digital health, or other high-dimensional data as appropriate to the portfolio and regulatory context.

• Practical understanding of artificial intelligence and machine learning and advanced analytics in regulated clinical development, including model development, validation, documentation, bias and assumption assessment, governance, explainability, and fit-for-purpose use in regulatory-relevant settings.

• Hands-on fluency in R and or Python, with working knowledge of SAS and SQL; ability to guide reproducible analyses, code quality, version control, reusable workflows, validated delivery practices, and inspection-ready documentation.

• Strong working knowledge of Clinical Data Interchange Standards Consortium standards and submission expectations, including Study Data Tabulation Model, Analysis Data Model, controlled terminology, Define-XML concepts, reviewer guides, traceability, data lineage, and submission-oriented data package requirements.

• Deep knowledge of the Food and Drug Administration, European Medicines Agency, Pharmaceuticals and Medical Devices Agency, National Medical Products Administration, Medicines and Healthcare products Regulatory Agency, International Council for Harmonisation - Good Clinical Practice, Good Clinical Practice, data privacy, inspection readiness, and traceability expectations relevant to clinical data, quantitative deliverables, and global submission packages.

• Ability to establish analytical standards, technical expectations, documentation practices, quality review approaches, and submission-readiness controls that enable scalable and inspection-ready delivery across multiple health authorities.

• Communicates complex quantitative findings clearly to scientific, operational, technical, executive, senior leadership, and health authority-facing audiences.

People Leadership & Behavioral Competencies

• Influences across functions without relying solely on direct authority; builds trusted partnerships with clinical, statistical, programming, data management, regulatory, technology, and vendor teams.

• Balances scientific rigor, speed, quality, resource capacity, regulatory risk, submission timelines, and practical delivery; proactively escalates risks with options and recommendations.

• Demonstrates curiosity, continuous improvement, sound judgment, and commitment to advancing modern clinical data science capabilities, developing others, and maintaining submission-ready standards.

• Leads with clarity, accountability, inclusion, and an enterprise mindset; creates an environment where team members can deliver, grow, collaborate, and uphold regulatory-quality expectations.

• Coaches and develops direct reports and matrixed contributors, providing actionable feedback, supporting career growth, and building future technical, regulatory, submission, and leadership capability.

At Takeda, we are transforming patient care through the development of novel specialty pharmaceuticals and best in class patient support programs. Takeda is a patient-focused company that will inspire and empower you to grow through life-changing work.

Certified as a Global Top Employer, Takeda offers stimulating careers, encourages innovation, and strives for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.

This position is currently classified as "hybrid" following Takeda's Hybrid and Remote Work policy.

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