Manager, Clinical Data Scientist

Lead clinical data science activities for assigned studies, delivering high-quality analyses, data visualization, and quantitative insights to support clinical development decisions.

Translate scientific and clinical questions into analysis-ready datasets, reproducible analytical workflows, and support integrated data review identifying trends and risks.

Contribute to automation, reusable analytics workflows, and fit-for-purpose AI/ML approaches while ensuring regulatory compliance and data quality.

PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or related field; or MS with 3+ years relevant experience.

Experience in quantitative analyses and data science within pharmaceutical, biotechnology, healthcare research, or regulated clinical development environments.

Proficiency in R and/or Python; working knowledge of SAS and SQL; familiarity with CDISC standards (SDTM, ADaM, Define-XML).

Work Experience Required: Not explicitly mentioned in the JD beyond educational qualifications and relevant experience requirement.

Strong foundation in clinical trial design, drug development, endpoints, biomarker data, and quantitative methods including longitudinal, survival, predictive modeling, and causal reasoning.

Experienced working with diverse data sources such as clinical trial, biomarker, real-world, imaging, digital health, aligned with regulatory requirements (FDA, EMA, ICH-GCP).

Skilled in applying AI/ML and advanced analytics in a regulated environment with ability to produce reproducible, traceable, high-quality deliverables and communicate quantitative findings clearly across cross-functional teams.