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Senior Manager, Statistics

Precision Life Sciences

Senior Manager, Statistics

Boston, MA
Full Time
Paid
  • Responsibilities

    Our client, in the biotechnology / life sciences industry, is seeking a Senior Manager, Statistics (contact to hire).

    The purpose of this position is to provide compound level/development phase statistical expertise and leadership by:

    • Independently designing, analyzing, and interpreting clinical or observational studies at a compound level for early phase or less complex programs.
    • Providing strategic statistical input for feasibility assessments, development plans, cross-study analyses, and regulatory submissions.
    • Improving and using standards to maximize global data integrability, interpretability, and compound level efficiency.
    • Leveraging internal and external resources to achieve a quality, timely and cost-effective compound level and submission deliverables.
    • They are independently representing the Statistics function in interactions with regulatory authorities.

    ACCOUNTABILITIES:

    • Independently represent statistics function on global teams in support of clinical or observational studies and compound level programs.
    • Provide strategic statistical input to feasibility assessments, development and submission plans, and defense of regulatory submissions. Negotiate timelines (statistical) at a compound level.
    • Plays a leadership role in developing and reviewing the study synopsis, protocol, statistical analysis plan, study report, and other regulatory submission documents, ensuring accurate and statistically valid deliverables.
    • Oversee definition and implementation of compound-level database (including derived database), analysis, and reporting standards. Improve or use existing standards to ensure maximization of global integrability and interpretability of data and enhance efficiency at a compound level. Coordinate with Data Management, Programming, Clinical, and PV to target high-quality databases and specifications at a compound level.
    • Plan and direct compound level analysis and reporting activities (eg, tables, listings, graphs) including work of other statisticians and programmers.
    • Identify compound-level vendor requirements and participate in the evaluation/selection of vendors. Provide compound-level analytical oversight of statistical activities of external vendors to ensure timeliness and quality of analysis data and statistical outputs. Review and approve key statistical vendor deliverables.
    • Identify and interact with external statistical experts for issues related to study design, methodology, and results.
    • Anticipate and communicate internal and external resource and quality issues that may impact deliverables or timelines of the compound level program. Propose and implement solutions. Escalate issues to management as appropriate in a timely manner.
    • Lead the implementation of department standards and process improvements.
    • Lead evaluation and implementation of alternative analysis methodology and data presentation techniques.
    • Monitor and contribute to industry advances in statistical methods to optimize study designs and statistical analysis methods, and implement innovative approaches at a compound level.

    EDUCATION, EXPERIENCE, AND SKILLS:

    • Ph.D. in statistics or biostatistics with at least 3 years of relevant experience or MS in statistics or biostatistics with at least 6 years of relevant experience..
    • Experience with advanced study design or at least one NDA/CTDs or other global regulatory submissions.
    • Advanced knowledge of clinical or observational study designs, common analysis methods, descriptive and inferential statistics.
    • Advanced knowledge of the pharmaceutical industry including the understanding of clinical drug development process and associated documents.
    • Extensive knowledge of FDA and ICH regulations and industry standards applicable to the design, analysis of clinical trials or observational research, and regulatory submissions.
    • Good knowledge of statistical programming languages (including SAS), software, techniques, and processes. Working knowledge of UNIX operating systems, and common software products and technologies used in conjunction with SAS (e.g., Microsoft Office products).
    • Excellent oral and written communication skills.
    • Strong project management skills.
    • Strong collaborative skills and ability to work with a cross-functional team.