Tech Stack

Description

You will perform end-to-end analysis of translational and clinical biomarker data from oncology clinical trials, applying rigorous statistical methods and collaborating with translational scientists to generate biologically meaningful insights that support clinical decision-making. This hands-on role focuses on direct analytical contributions to active clinical programs in a small, highly collaborative team.

Requirements

• PhD with 1+ years of relevant industry experience or Master's with 5+ years in Bioinformatics, Computational Biology, Genomics, Statistics, Cancer Biology, Immunology or related field
• Strong proficiency in R/Python for data analysis, statistical modeling, and visualization
• Experience working in Linux/Unix computing environments
• Solid foundation in statistics applied to biological and clinical datasets
• Knowledge of immunology and/or cancer biology

Responsibilities

• Perform end-to-end analysis of translational and clinical biomarker data including data preparation, QC, statistical analysis, and biological interpretation
• Analyze high-dimensional clinical trial datasets (bulk/single cell/spatial RNA-seq, protein biomarker platforms like MSD or Olink)
• Execute reproducible, well-documented analytical workflows ensuring data quality and analytical rigor
• Collaborate with translational scientists and cross-functional partners to interpret results in biological and clinical context
• Prepare clear figures, tables, and presentation materials to communicate findings for internal discussions, publications, and regulatory documents