Associate Principal Biostatistician Clinical Safety Statistics (css)

Merck Merck · Pharma · PA

This role provides statistical support and leadership for clinical safety data evaluation, collaborating with cross-functional teams throughout the drug development lifecycle. It involves designing, developing, and evaluating processes, methods, and tools for safety data analysis, and staying current with regulatory guidance and innovative statistical research.

What you'd actually do

  1. Provide statistical support and leadership for projects related to the evaluation of clinical safety data.
  2. Interact with cross-functional Risk Management Safety Teams (RMSTs) on planning and executing evaluations of safety data for clinical development programs. Serve as a statistical representative and core member on the RMST.
  3. Design, develop and evaluate processes, methods and tools for safety data evaluation.

Skills

Required

  • Solid knowledge of statistical analysis methodologies, including survival analysis, meta-analysis and Bayesian analysis methods.
  • Knowledge of and experience with clinical trial design and analysis.
  • Knowledge of and experience with the analysis and interpretation of (integrated) safety data.
  • Knowledge of and experience with the specifications, creation, and use of SDTM and ADaM datasets.
  • Solid knowledge of statistical and data processing software e.g. SAS and/or R and R-Shiny, including generation of statistical graphics.
  • Ability to function effectively in a team environment with personnel from different functional areas.
  • Strong oral and written communication, organizational, and project management skills.
  • Must also demonstrate a desire to learn, be proactive and motivated, and exhibit consistent focus on details and execution.

Nice to have

  • Knowledge of regulatory requirements regarding safety signal evaluation, identification, and reporting.
  • Knowledge of drug development process from Discovery, Preclinical Research, Clinical Trials (Phase 1, 2 and 3), NDA review, through Post-market safety monitoring.
  • An interest in statistical research activities particularly those related to the development and application of novel methods for safety data monitoring, evaluation, and benefit-risk assessment.
  • Publications in peer reviewed statistical/medical journals.
  • An understanding of disease biology and drug discovery and development.
  • Expertise with AI to facilitate writing (summaries, reports, manuscripts, etc.), programming, and other types of tasks.

What the JD emphasized

  • regulatory requirements