Manager, Clinical Data Scientist

October 8, 2026

Hybrid

Middle

Warsaw, Poland

Description

Takeda is hiring a Manager-level Clinical Data Scientist within Data and Quantitative Sciences to support clinical development programs. The role delivers analysis-ready data, quantitative analyses, visualizations, and interpretation summaries for assigned studies and workstreams. It applies modern clinical data science practices including automation, reusable analytics workflows, and approved AI and ML approaches, keeping scientific rigor and regulatory awareness central.

Responsibilities

Execute clinical data science activities for assigned studies or workstreams, helping deliver timely high-quality analyses, data review, and quantitative insights that support study goals
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 that need further review
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, helping ensure they meet established standards, processes, and quality expectations
Communicate risks related to data quality, analytical assumptions, timelines, and quantitative outputs to study leadership and functional team members
Contribute to continuous improvement through automation, reusable code, standard methods, and adoption of approved technologies and workflows

Requirements

PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or a related field; or a Master of Science with 3 or more years of relevant experience
Experience contributing to quantitative analyses and data science activities within pharmaceutical, biotechnology, healthcare research, or other regulated clinical development settings
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
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 different disciplines to achieve study goals
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 Clinical Data Interchange Standards Consortium standards, including Study Data Tabulation Model, Analysis Data Model, 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 artificial intelligence and machine learning and advanced analytics in regulated clinical development, including model development, validation, documentation, assumptions, bias considerations, and fit-for-purpose deployment
Awareness of Food and Drug Administration, European Medicines Agency, International Council for Harmonisation Good Clinical Practice, 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
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 artificial intelligence-enabled approaches

Conditions

Position is classified as hybrid following Takeda's Hybrid and Remote Work policy
Full time, regular employee position
Work location is Warsaw, Poland

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