Lead Statistical Programmer

Ensure accurate and timely completion of the statistical programming activities for assigned projects including verification and documentation of results.

• Participate in review of analysis plans and development of programming requirements.
• Provides statistical programming support for research projects, clinical development studies, and medical affairs/post-market activities by generating and verifying tables, figures and listings of medical data, according to study statistical analysis plans or project biostatisticians’ specifications.
• Assists in preparing manuscripts for publication, and data summaries for abstracts and posters at professional meetings and for Board presentations.
• Develops visualizations for high dimensional genomic data for patient reports and marketing materials.
• Participate in review of statistical analysis plans for the clinical studies by collaborating with biostatisticians, data managers and clinical trial managers to ensure programming integrity and compliance for data analyses and the reporting of the results.
• Exercises independent judgment in selecting and adapting methods appropriate for the specific objective.
• Contributes to development of best practices, policies and standards. Performs highly-complex programming to implement statistical methodologies developed by internal and external biostatisticians.
• Works on problems of diverse scope where data analysis requires evaluation of novel statistical techniques.
• Develops and maintains internal SAS macro library for statistical analysis and data display.
• Demonstrates good judgement in selecting fit-for-purpose methods and software tools for obtaining solutions.
• Participate or lead the departmental initiatives in developing the best practices and Standard Operating Procedures (SOPs) in Statistical Programming and Validation Standards.
• Directly supports project biostatistician with minimal guidance.
• Supports project biostatisticians on assigned clinical studies, research projects and marketing education by providing statistical programming for the statistical deliverables.
• Facilitates discussions with project biostatisticians to seek specification and clarification with minimal guidance.
• Oversee and project manage the activities of lower level personnel and contractors on assigned projects.
• Guide the lower level statistical programmers or contractors in the scientific area requirements and selecting appropriate methods and techniques.
• Liaise with vendors as needed to facilitate data transfer and statistical programming.
• Develop collaborative work environment and function as a positive role model for setting high expectations for quality, creativity and project ownership.

Genomic Health Inc. (An Exact Sciences Company) is seeking an exceptional individual with strong statistical programming and analytical skills to participate in the development, validation and post-marketing support of genomic biomarker assays that help cancer patients and their physicians make better treatment decisions. As a member of the Biostatistics team, the Lead Statistical Analyst/Programmer will collaborate across Genomic Health, working closely with Clinical Biostatistics, Data Management Operations, Clinical Development, Clinical Operations, Medical Communications, and Medical Affairs to provide expertise in the generation of statistical analyses, tables, figures and listings of medical data from diverse sources. A strong candidate will have extensive experience analyzing and developing visualizations for high dimensional data, preferably genomic data, knowledge of statistical theory including survival analysis and epidemiological methods and a minimum of 8 years of relevant work experience in industry or academia., Master’s degree in Computational or Biological Sciences, Chemistry or related discipline, or foreign equivalent, and five (5) years of experience in the job offered or in a closely related position.

Special Requirements: Requires an Advanced SAS certificate plus five (5) years of experience in each of the following:

• Statistical theory and statistical programming techniques and procedures such as SAS.
• Supporting highly visible statistical programming projects of clinical data with in a fast-paced environment.

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