Principal Statistical Programmer (R)

  • Contract
  • Remote

SimulStat

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Remote, 6-month contract with potential to extend long term

Principal Statistical Programmer (R)

Our client is dedicated to developing breakthrough therapies for neurodegenerative diseases through a deep commitment to degeneration biology and principles of translational medicine. We are seeking to recruit an experienced principal statistical programmer. The candidate will have the opportunity to help shape the client’s data and programming infrastructure, drive the adoption of R in a regulated environment, gain an in-depth understanding of drug development in a fast-moving industry environment and subject domain knowledge in the field of neurodegeneration.
The ideal candidate will have extensive experience supporting drug development and clinical study projects; will have excellent statistical programming and problem-solving skills; and will be able to function as an individual contributor. The candidate will take the initiative to stay current on technologies and methods, will champion the use of open-source software for clinical trial reporting, come up with innovative solutions to challenging problems, and work with Biometrics management to help set the overall strategic direction of the group. 

Primary Responsibilities

  • Represent Biometrics on projects and study teams.  Lead statistical programming deliverables including:  generation of data visualizations or summary reports to support internal decision making and regulatory interactions (IND/CTA filings, annual safety reporting, etc.); providing input for statistical analysis plans, study protocols and clinical study reports; reviewing study randomization specifications; collaborating with Clinical Data Management on case report form design, data review plans, and external data transfer specifications; collaboration with the study team to review data and manage timelines; oversight of Biometrics CRO deliverables.
  • Design, develop, and validate CDISC analysis data (i.e., SDTM, ADaM) for use with statistical reporting code and analytics applications.
  • Develop and manage reusable code for interactive data visualization, exploratory analysis, and statistical summaries in clinical study reports.
  • Work with the Biometrics Team to establish innovative processes to ensure high data quality, reporting of analysis results, and analysis reproducibility.
  • Support the Biometrics Team in efforts to build, maintain, and continuously improve an R infrastructure that is suitable for regulatory submission work.

Requirements

Must Have

    • At a minimum, a bachelor’s degree in Statistics, Biostatistics, Data Science, Mathematics, or related field.
    • At least 5 years of experience as a Statistical Programmer on a Biotech/Pharma Clinical Development Biometrics Team or with a similar team and experience supporting drug development, medical device development, or intervention studies.
    • Demonstrated ability to effectively lead projects and collaborate cross-functionally.
    • Exceptional R programming skills (including tidyverse, RMarkdown, Shiny, htmlwidgets, development of R packages, working with IT staff to build R infrastructure), experience applying software development concepts, well versed in reproducible research methods, and proficiency in using code repositories like Git/GitHub (or similar tools) for collaboration and versioning of operational, robust, and well documented code.
    • Able to work in a Linux/Unix environment (including shell scripting).
    • Applied experience with SDTM or ADaM CDISC data.
    • Demonstrated experience in creating compelling data visualizations to help teams make correct data driven decisions and effectively communicating results to team members.
    • Able to demonstrate a solid understanding of statistical principles and methods used in clinical study reports or scientific publication analyses.

Preferred

    • Prior work experience with experience with regulatory submission of CDISC data, clinical trials in the neuroscience field, working pharmacokinetic/pharmacodynamic data, proficiency in SAS and other languages (e.g., Python, Java, C++, MATLAB), experience with Amazon Web Services and cloud infrastructure, Docker containerization.

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