Drug Safety R&D (D SRD) is a global organization that provides input into drug target selection, helps identify promising drug candidates, develops biomarker and screening assays, and leads the conduct and interpretation of toxicology studies in support of clinical development programs. DSRD consists of many scientific disciplines, each generating critical data types for analysis and decision-making in the drug development process. Disciplines include general toxicology, pathology, safety pharmacology, genetic toxicology, developmental and reproductive toxicology, safety biomarkers, immunotoxicology, investigative toxicology, and computational sciences. Role Responsibilities
You will represent Biostatistics on cross-functional teams to provide effective statistical consultation with scientists and toxicologists. You will collaborate with scientific colleagues across a diverse set of disciplines in DSRD, on the design, analysis, and interpretation of nonclinical safety studies. You will be part of a team of nonclinical statisticians within Pfizer's Early Clinical Development (ECD) Biostatistics organization.
The position is located at the Groton, Connecticut site. There is no management of people in this role.
Ensure and implement statistically sound approaches for the design, analysis, reporting, and interpretation of exploratory, regulatory, and investigative nonclinical safety studies. Provide critical experimental design input for in vivo and in vitro studies. Develop automated statistical solutions to increase the efficiency of DSRD study conduct and reporting. Partner with other data science / computational groups to identify optimal solutions to scientific problems. Develop and deliver statistical training to scientists. Promote an effective Statistical network with other Pfizer statisticians. Promote statistical excellence and influence for all DSRD projects and products.Basic Qualifications
- M.S. in Statistics or Biostatistics with minimum 2 years' experience in an applied statistics setting, or Ph.D. in Statistics or a comparable quantitative field
- Programming in R (2+ years)
- Strong written and verbal communication skills.
- Demonstrated ability to work effectively as a part of an interdisciplinary team.
- Strong knowledge in general linear models, experimental design, probability, categorical data analysis, and Bayesian analysis
- Experience analyzing high-dimensional data; familiarity with machine learning methods
- R Shiny-app programming experience
- Proficiency with other statistical software (e.g., SAS, JMP, and GraphPad Prism)
- Familiarity with version control and collaborative programming (e.g., Git)
- Strong scientific background, with good working knowledge of biology, chemistry, pharmacology, or toxicology.
Relocation support available
Work Location Assignment:Flexible
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