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Added 8 mins ago
PS
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Roche

Principal Bioinformatics Scientist I

Mississauga, ON, Canada
Canada Pharma Campus, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 8, 2026

Original job description

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.
Best Practices: Enforce high-standard software engineering practices, including Git version control, continuous integration, unit testing, and modular architecture.

Who You Are

Education & Experience: Master’s degree with 7+ years of related experience; OR Ph.D. with 4+ years of related experience (work experience can be prior or post-grad; relevant post-grad academic lab training will be considered).
Matrixed Collaboration & Stakeholder Management: Proven ability to partner seamlessly across multidisciplinary teams - including wet-lab scientists, software engineers, lab directors, and Quality assurance - to align technical specs with clinical goals.

Technical Mastery

Deep understanding of high-throughput sequencing data analysis across various modalities (targeted panels, WGS/WES, transcriptomics, or liquid biopsy/ctDNA).
Proficient in Python/R/C++ and Linux/Bash alongside hands-on experience using workflow managers (Nextflow) and containerized software deployments.
Modern Workflow Adaptability: Proven ability to leverage AI development tools to maximize productivity, alongside excellent communication skills suited for navigating complex, cross-functional organizational environments.

Relocation benefits are not available for this position.

The expected salary range for this position based on the primary location of Mississauga is 115,328.00 and 151,368.00 of hiring range. Actual pay will be determined based on experience, qualifications, and other job-related factors as determined by the company.

We use artificial intelligence to screen, assess or select applicants for this role.

This posting is for an existing vacancy at Hoffmann-La Roche Ltd.

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.

Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.

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More about this job

Responsibilities

The role involves designing, optimizing, and validating NGS data processing pipelines and algorithms for clinical diagnostics. You will collaborate with cross-functional teams to translate complex genomic data into actionable health insights while ensuring regulatory compliance.

Requirements

Candidates must hold a Master's degree with 7+ years of experience or a Ph.D. with 4+ years of experience in a relevant field. Proficiency in Python, R, C++, and bioinformatics workflow managers like Nextflow is required.

Skills

Bioinformatics
NGS
Python
R
C++
Nextflow
Docker
Singularity
Statistical modeling
Genomics
Clinical diagnostics
Algorithm development
Data analysis
Linux
Bash
Quality management systems

Visa sponsorship

Not detected in the job text

Keywords

Bioinformatics
NGS
Nextflow
Docker
Singularity
Python
R
C++
Linux
Bash
Genomics
Clinical diagnostics
Precision medicine
Statistical modeling
Artificial intelligence
Cloud computing
Quality management systems
CAP/CLIA
Algorithm development
Data analysis
Software engineering
Assay development
Transcriptomics
Liquid biopsy
WGS
WES
Git
Continuous integration
Unit testing
Modular architecture

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