Senior Research Statistician - Statistical Innovation (Hybrid)
About The Position
The Senior Research Statistician in Statistical Innovation provides scientific and statistical leadership for initiatives focused on designing innovative clinical trials. The role evaluates, develops, and deploys advanced and novel statistical and analytical modeling and simulations to advance statistical innovation in Clinical Development. The position supports the evaluation, introduction, development, and education of novel statistical and machine learning or deep learning approaches. It investigates complex innovative designs and analysis options using scientific computing, modeling, and simulations, and applies emerging statistical methods to solve real-world problems. The role also develops, implements, and rolls out statistical and deep learning tools and techniques to operationalize innovative methodologies, and builds an external reputation through industry presentations, meetings, and peer-reviewed publications.
Requirements
- PhD in Statistics, Biostatistics, or a highly related field.
- Advanced knowledge of statistical modeling and methodology and a good understanding of the drug development process.
- Demonstrated experience in advanced statistical computing and simulation.
- Proven expertise in standard statistical software, such as SAS and R.
- Ability to collaborate and consult with discipline experts and leaders within and across functions.
- Excellent oral and written communication skills.
- Excellent teamwork and leadership skills.
- Passion for statistical innovation, out-of-the-box thinking, and challenging the status quo.
Nice To Haves
- Experience in pharmaceutical development and applied statistics or statistical consulting.
- Expertise in specialized statistical software, such as FACTS or EAST.
Responsibilities
- Support the evaluation, introduction, development, and education of novel statistical and machine learning or deep learning approaches.
- Investigate and evaluate complex innovative designs and analysis options using scientific computing, modeling, and simulations.
- Acquire and apply knowledge of advanced and emerging statistical methods, including adaptive designs, Bayesian methods, synthetic control, and predictive modeling.
- Create and implement new or improved approaches, alternatives, and ideas in modeling and simulations.
- Apply statistical knowledge to real-world problems and evaluate alternative statistical and machine learning approaches.
- Develop, implement, and roll out statistical and deep learning tools and techniques, using tools such as R, R-Shiny, Python, and Julia, to operationalize innovative methodologies.
- Build and maintain an external reputation and influence the industry through presentations, industry meetings, and peer-reviewed publications.
Benefits
- Paid time off, including vacation, holidays, and sick time.
- Medical, dental, and vision insurance for eligible employees.
- 401(k) for eligible employees.
- Eligibility to participate in short-term incentive programs.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
