Senior Clinical Data Science Manager — Hybrid & AI/ML

Takeda Pharmaceutical Co.; Warszawa; Hybrid; PLN 300,000 - 520,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Takeda Pharmaceutical Co. in Warsaw, Poland is seeking a Senior Manager-level Clinical Data Scientist.

You will apply statistical and data science methods to support clinical development programs and partner with cross-functional teams to deliver analysis-ready data and insights. You will drive modern practices with automation, reusable analytics workflows, and AI/ML-enabled approaches while upholding scientific rigor, regulatory awareness, and patient-centered decision making.

Qualifications

• PhD or MS with substantial experience in clinical data science and statistics.
• Experience supporting quantitative analyses in regulated clinical development environments.
• Ability to communicate evidence clearly to diverse stakeholders.

Responsibilities

• Apply statistical and data science methods to support clinical development programs.
• Partner with cross-functional teams to deliver analysis-ready data and insights.
• Develop automated analytics workflows and AI/ML-enabled approaches.
• Ensure data quality, traceability, and reproducibility of analyses.
• Translate clinical questions into reproducible analytical datasets and workflows.
• Support submission-ready data and documentation.

Skills

Statistical analysis

Data science

Cross-functional collaboration

Regulatory awareness

Communication of findings

Education

PhD in statistics/biostatistics/data science or related field

MS with 7+ years of relevant experience

Tools

R

Python

SAS

SQL

CDISC (SDTM/ADaM)

Job description

Takeda Pharmaceutical Co. in Warsaw, Poland is seeking a Senior Manager-level Clinical Data Scientist.

You will apply statistical and data science methods to support clinical development programs and partner with cross-functional teams to deliver analysis-ready data and insights. You will drive modern practices with automation, reusable analytics workflows, and AI/ML-enabled approaches while upholding scientific rigor, regulatory awareness, and patient-centered decision making.