Principal Scientist, Applied and Translational Omics

This role focuses on leading applied and translational omics analyses that turn complex biological data into clear decisions. The scientist will partner with experimental teams, data engineers, and clinical groups to create analyses and merge multi-omic data with clinical information.

Key Responsibilities

• Design reproducible analyses for genomic, transcriptomic, and proteomic datasets
• Combine multi-omic and clinical data to identify targets and biomarkers
• Develop and validate analysis pipelines
• Mentor junior scientists
• Apply statistical methods and machine learning to translational challenges

Basic Qualifications

• Advanced degree (Master's with experience or PhD) in computational biology, bioinformatics, genetics, or biostatistics
• R and/or Python programming experience
• Large omics dataset processing and analysis background
• Knowledge of genomics file formats (VCF, BAM/FASTQ, single-cell structures)
• Version control and reproducible research experience
• 1+ years single-cell and spatial omics workflow experience

Preferred Qualifications

• Multidisciplinary team collaboration
• Omics-clinical data integration
• Pipeline productionization experience
• Publications or significant project contributions
• Statistical modeling and hypothesis testing expertise
• Biomarker assessment experience
• Clinical trial data analysis background