Job Description:
Job Summary
The Senior Manager, Biostatistics provides technical leadership and biostatistical expertise in the design, execution, analysis, and interpretation of clinical trial data. This role supports program-level statistical strategies, oversees study-level analyses, and contributes to regulatory submissions and departmental process improvements. The position plays a critical role in ensuring statistical integrity and compliance across clinical development programs while collaborating with cross-functional teams to support decision-making and data-driven strategies.
Key Responsibilities
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Design, evaluate, and interpret clinical trial data, providing statistical input throughout study planning and execution.
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Draft and review statistical analysis plans (SAPs), tables, listings, and figure (TFL) specifications.
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Review case report forms (CRFs) and other key study documents to ensure statistical alignment.
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Manage and oversee CRO statistical activities, including validation of outputs and deliverables.
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Generate and review study randomization files and contribute to protocol and IDMC charter development.
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Present and interpret statistical results, author statistical sections for clinical study reports (CSRs) and publications.
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Support regulatory responses, submissions, and reimbursement-related data packages.
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Provide statistical input to inform clinical development strategies, interim analyses, and innovative study designs.
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Contribute to advanced statistical research and methodological innovation within the department.
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Participate in establishing and maintaining departmental standards, procedures, and training.
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Collaborate cross-functionally to ensure data integrity and consistency across programs.
Qualifications
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PhD in Biostatistics or Statistics with 5+ years of relevant pharmaceutical experience, or Masters degree with 7+ years of experience.
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Strong foundation in biostatistical methods for clinical trials and related study designs.
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Proven experience in authoring SAPs, TFL specifications, and validating statistical outputs.
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Knowledge of CDISC standards (SDTM, ADaM) and relevant controlled terminologies.
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Familiarity with regulatory guidance documents (ICH, FDA, EMA).
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Proficient in SAS and experienced with R or Python.
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Excellent organization, problem-solving, and multitasking skills.
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Strong communication and collaboration skills in a cross-functional environment.
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Experience with longitudinal data analysis, adaptive design, and advanced methods involving real-world data, machine learning, or AI is preferred.