Hiring.Camp

Manager, Clinical Data Scientist

Takeda

·

2 weeks ago

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Location
POL - Warsaw, Poland
Workplace
Hybrid
Type
Full-time
Department
Healthcare
Seniority
Manager
Education
PhD
Source
Workday

Description

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

About the role:


At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on four therapeutic areas and other targeted investments, we push the boundaries of what is possible in order to bring life-changing therapies to patients worldwide.


You will serve as a Manager-level Clinical Data Scientist within Data and Quantitative Sciences, using statistical, data science, and analytical methods to support clinical development programs. You will work with cross-functional study teams to deliver analysis-ready data, quantitative analyses, visualizations, and interpretation summaries for assigned studies or workstreams. You will support fit-for-purpose statistical, data science, and advanced analytics activities under the direction of study and functional leadership.


You will also collaborate with team members to help ensure high-quality, traceable, analysis-ready, and submission-ready data. In this role, you will apply modern clinical data science practices, including automation, reusable analytics workflows, and approved artificial intelligence and machine learning approaches, while keeping scientific rigor, regulatory awareness, and patient-focused decision making at the center of your work.


How you will contribute:


• 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.


Minimum Requirements/Qualifications: 


• 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, Good 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.


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.


#LI-Hybrid

#LI-AA1

Locations

Warsaw, Poland

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Skills

PythonSQLMachine LearningData SciencePatient Care

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