Senior Scientific Software Engineer, Analytics and Workflows

Roche • South San Francisco, CA

4d • $142,500 - $264,700 • Hybrid

About The Position

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Analytics and Workflows group within the Center of Excellence (CoE) is dedicated to turning complex data into actionable insights that advance drug discovery and development. We leverage cutting-edge high-throughput technologies and foundational multimodal machine learning models to analyze large-scale biological data, enabling deeper understanding of disease mechanisms and the identification of novel therapeutic opportunities. Despite advances in these fields, however, transforming raw data and computational models into meaningful biological insights remains a key challenge. In this role, you’ll work at the intersection of data science, biology, and engineering to build innovative analytical tools that bridge the gap between data generation and biological interpretation—helping unlock new avenues for scientific discovery and impact.
The Opportunity: Genentech seeks a talented and highly motivated Bioinformatics Software Engineer with expert knowledge of reproducible and scalable analysis of proteomics and genomic datasets for target and biomarker discovery. The primary focus of this position is to establish new and maintain existing workflows, libraries and visualizations for the analysis and QC of proteomics and genomics data. You will evaluate, refine, and productionize analytical workflows that enable our scientists to interrogate biology and make drug pipeline relevant decisions. You are facilitating data reuse, multi-modal analyses and AI/ML efforts by fostering the adoption of standardized data formats and repositories. You will deeply engage with computational scientists to understand their analytical needs and turn these into reusable components. To achieve this outcome you confidently evaluate and combine open-source, commercial and in-house developed solutions and combine them into reliable, cutting edge applications. A successful candidate will collaborate with interdisciplinary teams of Software Engineers, Computational Biology and Data Scientists to develop scientific workflows and tools that make data available to machines and humans using a variety of interfaces.

Requirements

• PhD in Software Engineering, Computer Science, Bioinformatics, or similar and 2 years of relevant experience in a clinical, academic or commercial setting, OR a Masters degree or equivalent and at least 5 years of relevant experience.
• Successfully analyzed complex biological datasets using a modern data science framework.
• Familiarity with major tools and statistical methods used during the analysis of various omics modalities.
• Expert knowledge of proteomics analysis and ability to rapidly identify, diagnose and mitigate unlikely or surprising results.
• Successfully delivered a software project throughout the whole development cycle (planning, implementation, testing, release, maintenance) following modern software development practices.
• Using AI expert assistance in all stages of your work.
• Comfortable working with MCPs, REST APIs and other modern data science programmatic interfaces.
• Abundant experience in managing FAIR data as well as tracking data lineage, ensuring data quality and improving data discovery.
• Ability to break down large problems into smaller software components and develop them independently or as part of a large team.
• Comfortable working both independently and collaboratively, and with handling several concurrent, fast-paced projects.

Nice To Haves

• Experience with Bioconductor and the Tidyverse ecosystem.
• Experience with RMarkdown / Quarto, and Shiny and Plumber deployment.
• Experience with Python technologies (e.g. Pandas, Polars, Streamlit, FastAPI).
• Prior experience in a life science or drug development environment.

Responsibilities

• Establish new and maintain existing workflows, libraries and visualizations for the analysis and QC of proteomics and genomics data.
• Evaluate, refine, and productionize analytical workflows that enable scientists to interrogate biology and make drug pipeline relevant decisions.
• Facilitate data reuse, multi-modal analyses and AI/ML efforts by fostering the adoption of standardized data formats and repositories.
• Deeply engage with computational scientists to understand their analytical needs and turn these into reusable components.
• Evaluate and combine open-source, commercial and in-house developed solutions and combine them into reliable, cutting edge applications.
• Collaborate with interdisciplinary teams of Software Engineers, Computational Biology and Data Scientists to develop scientific workflows and tools that make data available to machines and humans using a variety of interfaces.

Benefits

• Access to large data sets, samples and compute resources.
• Access to state-of-the-art technologies and pioneering research.
• Participation in seminar series featuring academic and industry scientists.
• Campus-like lifestyle with a healthy work-life balance.
• Mentored opportunities to further develop professional skills.
• Discretionary annual bonus may be available based on individual and Company performance.
• Benefits detailed at the link provided below.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree