The Principal Biostatistician will lead Phase I-IV clinical studies, providing strategic statistical guidance and developing study protocols. They will also utilize advanced statistical methods, machine learning, and deep learning to analyze data and automate processes for clinical development.
Who Are You?
An experienced Principal Biostatistician with a passion for clinical development and analysis, adept at utilizing advanced statistical methods, you will lead one Phase I-IV clinical studies across your region. You are excited and enthusiastic, motivate your teams to do great work and collaborate easily with your clients. You never settle for what is, but always push clinical development forward to what it could be. You motivate others to do the same.
Sponsor-dedicated:
Working fully embedded within one of our pharmaceutical clients, with the support of Cytel right behind you, you'll be at the heart of our client's innovation. As a Biostatistician you will be dedicated to one of our global pharmaceutical clients; a company that is driving the next generation of patient treatment, where individuals are empowered to work with autonomy and ownership. This is an exciting time to be a part of this new program.
Position Overview:
Our Principal Biostatisticians provide statistical and development support and influence for the associated client's trials providing expertise into processes, clinical development plans, concept sheets and protocols, as well as potentially providing oversight of work supported by other vendors. You will formulate integrated analytical approach to mine data sources, employ statistical methods, machine learning & deep learning algorithms to discover actionable insights and automate process for reducing effort and time for repeated use.
Responsibilities
Participating in the development of study protocols, including study design discussions and sample size calculations.
Participating in exploratory data analyses to evaluate emerging study trends, support scientific decision-making, and generate insights throughout the course of development.
Applying advanced statistical methodologies, including mixed models and other complex modeling techniques, to support efficacy and longitudinal analyses.
Designing and executing simulation studies to evaluate study designs, operating characteristics, and statistical methodologies.
Leading and contributing to efficacy analyses and interpretation of primary and secondary endpoints.
Reviewing CRFs and data review guidelines; developing Statistical Analysis Plans (SAPs), including analysis dataset and TLF specifications.
Performing statistical analyses and interpreting statistical results.
Leading study activities when called upon and providing strategic statistical guidance to cross-functional teams.
Utilizing strong communication skills to present statistical methodology, assumptions, and the implications of decisions in clear, non-technical language.
Serving as a collaborative team player with a willingness to go the extra distance to meet project goals and timelines.
Demonstrating adaptability and flexibility as project priorities evolve.
Qualifications
Here at Cytel we want our employees to succeed and we enable this success through consistent training, development and support. To be successful in this position you will have:
Master's degree in Statistics, Biostatistics, or a related discipline. PhD strongly preferred.
8-10 years of biostatistics experience supporting clinical trials within the pharmaceutical or biotechnology industry. CRO experience strongly preferred.
3-5 years of Study Lead experience working with cross-functional development teams.
Extensive experience in study design, sample size determination, protocol development, SAP development, efficacy analyses, and preparation of clinical study reports, including integrated summaries for regulatory submissions (ISS/ISE).
Strong knowledge and practical application of advanced statistical methods, including mixed models, longitudinal analyses, and simulation methodologies.
Demonstrated experience performing exploratory statistical analyses to support clinical development and decision-making.
Strong proficiency in R for statistical analyses, simulations, data visualization, and advanced modeling.
Solid SAS programming skills, including QC of critical outputs, efficacy and safety tables, and close collaboration with Statistical Programmers.
Strong knowledge of ICH guidelines and regulatory expectations.
Solid understanding and implementation of CDISC standards for regulatory submissions.
Experience generating ADaM specifications and performing programmatic review of analysis datasets.
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