Data Scientist II

Respnsibilities:

• Partner with statisticians in writing, reviewing and executing statistical analysis plans (SAP) for biomarkers, highlighting the biomarker strategy for clinical drug development.
• Plan and perform relevant and innovative statistical analyses of high-dimensional (e.g. gene expression, single cell sequencing, spatial transcriptomics) data generated by cutting edge technologies.
• Create and perform end-to-end analyses that include design, data gathering, processing, analysis, iteration with stakeholders, and presentation of results.
• Accountable for the development of data analytics tools, visualization platforms, predictive models, and emergent insight capabilities that make use of complementary and complex data sets.
• Communicate with internal and external scientific communities, bringing forth innovative approaches to biomarkers and drug development.

Requirements:

• MS or PhD in Bioinformatics, Computational Biology, Statistics, Biological Sciences, Cancer Biology, Genetics, Genomics, Computer Science, Physics, or similar field.
• MS with 3+ years of experience or PhD with 1+ years of experience in molecular diagnostics or pharmaceutical industry experience will be considered, experience performing benchwork preferred.
• Experience with analysis of large scale PK/PD, genomic, and proteomic data sets.
• Experience in modeling methods particularly in their application to Pharmaceutical R&D.
• Experience interpreting biological statistics and translating them to clear relationships of clinical outcomes for clinical and business stakeholders.
• Knowledge of molecular biology, understanding of disease pathways, and bioanalytical assays.
• Strong problem-solving and collaboration skills, and rigorous and creative thinking.
• Strong verbal, writing, and presentation skills.
• Ability to succeed and thrive in a rapid paced and cross-functional team environment.
• Experience programming in Python or R is a must, Tableau or Spotfire is desirable.