Senior Manager, Clinical Data Scientist - Statistics

Takeda; Warszawa; Hybrid; PLN 350,000 - 600,000; Full time

Job summary

Takeda in Warsaw, Poland, seeks a Senior Manager-level Clinical Data Scientist to apply statistical and data science methods across clinical development, delivering analysis-ready data and quantitative insights.

You will collaborate with cross-functional teams to advance reproducible analytics, automation, and AI-enabled approaches while upholding regulatory standards and patient safety.

Qualifications

• PhD in statistics/biostatistics/data science or related field with 3+ years of relevant experience.
• Experience supporting quantitative analyses and data science activities within regulated clinical development.
• Demonstrated ability to contribute to clinical development decisions through quantitative analysis and clear communication of evidence.
• Experience working on cross-functional study teams and collaborating across disciplines to achieve study objectives.
• Experience with clinical trial data and at least one additional data type such as biomarker, real-world, external, imaging, or digital health.
• Strong knowledge of clinical trial design, endpoints, estimands, biomarkers, data interpretation, and analytics in clinical decision making.
• Proficiency in R and/or Python; working knowledge of SAS and SQL.

Responsibilities

• Perform exploratory analyses, data visualizations, and quantitative assessments using diverse data sources.
• Apply statistical, machine learning, simulation, and visualization methods to help interpret study results and inform decisions.
• Translate questions into analysis-ready datasets, specifications, and reproducible workflows.
• Deliver clinical data science activities for assigned studies, including timely analyses and quantitative insights.
• Support integrated data review by identifying data trends, inconsistencies, and risks needing review.
• Review analysis outputs and technical documentation to ensure quality and reproducibility.
• Collaborate with Clinical Data Management, Pharmacology, PSPV, Operations, and Translational Sciences to support study objectives.
• Share technical expertise and mentor less experienced team members.
• Contribute to departmental standards, process improvements, and technology adoption initiatives.
• Support continuous improvement through automation and reusable code.

Skills

R

Python

SAS

SQL

Machine learning

Statistics

Clinical data analysis

Cross-functional collaboration

Education

PhD in statistics/biostatistics/data science or related field

Master's degree with 6+ years experience

Tools

SAS

Python

R

SQL

Job description

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 Data Model, controlled terminology, Define-XML concepts, and submission-oriented data expectations.
• Knowledge of Food and Drug Administration, European Medicines Agency, International Council for Harmonisation Good Clinical Practice, GxP, data privacy, inspection readiness, and traceability expectations relevant to clinical data and quantitative deliverables.
• Practical understanding of artificial intelligence and machine learning in regulated clinical development, including model development, validation, documentation, assumptions, bias considerations, and fit-for-purpose deployment.
• Familiarity with modern data platforms, reusable analytics workflows, automation, metadata-driven processes, and governed data standards.
• Ability to develop clear analysis specifications, visualization approaches, documentation, and interpretation summaries for scientific, operational, and study team audiences.

Additional Preferred Competencies

• Communicates quantitative findings clearly to scientific, operational, technical, and leadership audiences.
• Builds effective working relationships across study teams and functional partners.
• 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.
• Demonstrates strong technical credibility, sound judgment, and collaborative problem‑solving skills.
• Embraces continuous learning and adoption of new analytical methods, automation, and artificial intelligence enabled approaches.

More about us

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.

Locations

Warsaw, Poland

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time