Principal Bioinformatics Scientist I

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

Principal Bioinformatics Scientist I

This role is a vital part of our Bioinformatics team, which is committed to advancing precision medicine by building cutting-edge computational tools for clinical diagnostics. As a member of this team, you will sit at the dynamic intersection of computational biology, assay development, and software engineering to translate complex genomic data into actionable health insights.

You will have the opportunity to collaborate closely with cross-functional partners across Wet-Lab Assay Development, Software Engineering, CLIA Operations, and Quality to design, validate, and operationalize next-generation diagnostic tests.

The Opportunity

As a Bioinformatics Scientist, you will lead the design, optimization, and clinical validation of innovative NGS data processing pipelines and algorithms. You will serve as the technical bridge between wet-lab innovation and production-grade software engineering, leveraging advanced statistical modeling and modern AI coding tools to deliver high-accuracy molecular diagnostics for patient care.

- Pipeline & Algorithm Development: Design, benchmark, and optimize scalable, reproducible NGS bioinformatics pipelines using Nextflow, Docker/Singularity, and cloud environments.

- Analytical Validation: Partner with Assay Development and CLIA lab teams to establish statistical analysis plans and validate novel diagnostic assays (ensuring high sensitivity, specificity, and precision).

- AI-Accelerated Engineering: Routinely integrate AI coding tools and automated workflows to accelerate algorithm development, refactoring, and data analysis.

- Production Translation: Draft clear functional and technical specifications to guide software engineering teams in transitioning research prototypes into robust clinical software.

- Quality & Regulatory Compliance: Implement sample- and run-level statistical QC metrics while maintaining thorough QMS-compliant documentation for CAP/CLIA audits.