Manager, Clinical Data Scientist

Job Title: Manager, Clinical Data Scientist Company: Takeda Job Category: Data Science Roles & Responsibilities: Job Description: Objective / Purpose: * Serve as a Manager\-level Clinical Data Scientist within Data \& Quantitative Sciences, applying statistical, data science, and analytical methods to support clinical development programs. * Contribute to cross\-functional study teams by delivering analysis\-ready data, quantitative analyses, visualizations, and interpretation summaries for assigned studies or workstreams. * Support fit\-for\-purpose statistical, data science, and advanced analytics activities under the direction of study and functional leadership. * Collaborate with cross\-functional team members to support high\-quality, traceable, analysis\-ready, and submission\-ready data. * Apply modern clinical data science practices, including automation, reusable analytics workflows, and approved AI/ML\-enabled approaches, while maintaining scientific rigor, regulatory awareness, and patient\-focused decision making. Accountabilities: * Execute clinical data science activities for assigned studies or workstreams, 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. * Translate scientific and clinical questions into analysis\-ready datasets, analysis specifications, and reproducible analytical workflows with guidance from senior team members. * 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. * Review and contribute to outputs produced by internal teams and external partners, ensuring adherence to established standards, processes, and quality expectations. * Communicate risks related to data quality, analytical assumptions, timelines, and quantitative outputs to study leadership and functional stakeholders. * Contribute to continuous improvement efforts through automation, reusable code, standard methodologies, and adoption of approved technologies and workflows. Highest\-priority Technical Skills: * Working knowledge of clinical trial design, drug development, endpoints, estimands, biomarkers, data interpretation, and the role of analytics in clinical decision making. * Solid 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; ability to develop and support reproducible analyses, code quality, version control, and validated workflows. * Working knowledge of CDISC standards, including SDTM, ADaM, controlled terminology, Define\-XML concepts, and submission\-oriented data expectations. * Ability to integrate, analyze, and interpret diverse data sources, including clinical trial, biomarker, real\-world, external, imaging, digital health, or high\-dimensional data as appropriate to assigned studies. * Practical understanding of AI/ML and advanced analytics in regulated clinical development, including model development, validation, documentation, assumptions, bias considerations, and fit\-for\-purpose deployment. * Awareness of FDA, EMA, ICH\-GCP, GxP, data privacy, inspection readiness, and traceability expectations relevant to clinical data and quantitative deliverables. * Ability to create clear analysis specifications, visualization approaches, documentation, and interpretation summaries suitable for scientific, operational, and study\-team audiences. * Familiarity with modern data platforms, reusable analytics workflows, automation, metadata\-driven processes, and governed data standards. Behavioral Competencies: * Communicates quantitative findings clearly to scientific, operational, technical, and study\-team audiences. * Builds effective working relationships across study teams and functional partners. * Demonstrates technical credibility, sound judgment, and collaborative problem\-solving skills. * Balances scientific rigor, quality, and timely delivery while proactively communicating risks and issues. * Demonstrates accountability for assigned deliverables and commitment to reproducible, traceable, high\-quality work. * Embraces continuous learning and adoption of innovative analytical methods, automation, and AI\-enabled approaches. Locations: IND \- Bengaluru \- Research and Development Work Location: Bengaluru, Karnataka, India Availability: Full time

Education \& Competencies (Technical and Behavioral): Education / Experience: * PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or related field; or MS with 3\+ years of relevant experience. Equivalent combinations should be reviewed with HR. * Experience contributing to quantitative analyses and data science activities within pharmaceutical, biotechnology, healthcare research, or other regulated clinical development environments. * Demonstrated ability to support clinical development decisions through quantitative analysis, data interpretation, and clear communication of evidence. * Experience working effectively on cross\-functional study teams and collaborating across functional 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. Key Skills: Data Science Salary: Not disclosed