Teams at Cytel

Leads biomedical data science for clinical and health research, integrating clinical, observational, EHR, genetic, wearable, electrophysiological, and video data. Develops signal-processing methods, machine-learning models, probabilistic and time-series analyses, scalable data pipelines, and reproducible workflows. Validates clinically relevant models, supports disease phenotyping and predictive modeling, ensures compliance with pharmaceutical and healthcare standards, and communicates technical findings to clients and stakeholders.

Provides statistical support for Phase I–IV clinical studies, including study design, sample size calculations, protocol development, CRF and data review, SAPs, ADaM specifications, statistical analyses, clinical study reports, and regulatory submissions. Collaborates with clinical, regulatory, programming, pharmaceutical, and biotechnology teams while explaining statistical methods and results to stakeholders.

Supports risk-based quality management for clinical studies by assessing protocol risks, implementing KRIs and QTLs, analyzing clinical trial data, identifying anomalies and issues, maintaining RBQM systems, documenting processes, conducting quality control, and communicating risks to cross-functional study teams. The role also supports inspection readiness and collaborates with programmers on study-specific analytics, visualizations, and system configuration.