Associate Director - Early Clinical Development, Nonclinical Statistics
Responsible for ensuring sound statistical thinking and methods are utilized in the design, analysis, and statistical interpretation of studies focused on oncology preclinical and translational research.
Collaborate with various scientists in the design, analysis and reporting of biological and ‘omics data from target identification, assay development, in silico, in vitro and in vivo studies, including statistical interpretation of published or internally generated results in order to inform decision-making.
Interact with translational assay lead, research project lead and external experts to assure sound quantitative approaches are applied to data collection and analysis.
Work with an interdisciplinary team of molecular and computational biologists to develop statistical and computational methods to analyze high-throughput immune phenotyping, genomics, and therapeutic response data from pre-clinical experiments and clinical samples for novel immune-oncology targets, combination opportunities, and biomarkers of response.
Build tools and pipelines for both scientists and statisticians to perform routine analysis, to report and visualize data and to support large-scale ‘omics data analysis. Develop and provide statistical trainings to scientists.
Use statistical expertise to influence both internal and external reports and presentations, with the aim to improve the quality of internal decision making and increase our influence on the external environment.
MSc in Statistics (PhD preferred) or related mathematical field, or demonstration of sufficient statistical training to be successful in the position, including at least 5-8 years' pharmaceutical industry experience or academic training in genomics and translational research.
At least three years of experience applying statistical methods to the prospective design and analysis of scientific and/or clinical problems. Pharmaceutical or biotech applications desired.
Experience running simulations and developing statistical methodology.
Experience with multivariate statistics and statistical methods to quantify uncertainty in multi-dimensional data, and with QC procedures for translational and sequencing data.
Either experience in using or sound understanding of the value of Bayesian methods to scientific research.
Demonstrated strong communication skills, both oral and written.
Demonstrated ability to work effectively as a part of a team.
Technical Skill Requirements
Must have proficient R programming skills and familiarity with a Linux/UNIX environment
Must be able to explain statistical techniques and considerations to non-statisticians
Other Job Details
Eligible for Relocation Package
Eligible for Employee Referral Bonus
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