Statistics And Data Management Lead Biostatistician

Key Responsibilities

• Study Design and Statistical Analysis: Provides statistical expertise in designing clinical trials, bioequivalence studies, and observational research, including determining study endpoints, sample size, statistical power, and appropriate analytical methodologies. Conducts and reviews statistical analyses and interprets study results to ensure scientific validity and reliability.
• Bioequivalence and Clinical Study Evaluation: Reviews raw data and biostatistical components of bioequivalence study reports for externally sourced finished goods (ESFG). Evaluates statistical methodologies, results, and compliance with applicable regulatory requirements.
• Real-World Evidence and Advanced Analytics: Designs and analyzes observational and real-world evidence studies using appropriate statistical methodologies, including propensity score matching, survival analysis, and predictive modeling. Generates insights to support evidence synthesis, medical strategy, and portfolio decisions.
• Regulatory and Cross-Functional Support: Prepares and reviews statistical components of regulatory submission dossiers and responses to regulatory queries. Collaborates with Clinical, Medical, Regulatory, and Product Development teams to provide statistical insights on study feasibility, evidence gaps, and product development strategies.
• Data Governance and Capability Development: Ensures data integrity, quality, and compliance with applicable regulatory guidelines, Good Clinical Practice (GCP), and internal standards. Establishes statistical processes and standards, develops data visualization tools, and promotes statistical capabilities and the adoption of emerging analytical methodologies.
  
  

• Bachelor's degree in Statistics, Biostatistics, Mathematics, or other related quantitative disciplines; Master's degree is an advantage.
• Relevant experience in biostatistics, clinical research, statistical analysis, or pharmaceutical research and development.
• Knowledge of clinical trial design, bioequivalence assessment, and statistical methodologies for observational and real-world evidence studies.
• Proficiency in statistical programming tools such as SAS and/or R.
• Familiarity with ICH guidelines, Good Clinical Practice (GCP), PFDA requirements, and regulatory submission processes.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Experience in data visualization tools such as Power BI and advanced analytics is an advantage.