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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.

Who You Are:

• You have a PhD in Software Engineering, Computer Science, Bioinformatics, or similar and 2 years of relevant experience in a clinical, academic or commercial setting. Alternatively, a Masters degree or equivalent and at least 5 years of relevant experience.

• You have successfully analyzed complex biological datasets using a modern data science framework and are familiar with major tools and statistical methods used during the analysis of various omics modalities. 

• You have expert knowledge of proteomics analysis and can rapidly identify, diagnose and mitigate unlikely or surprising results.

• You have successfully delivered a software project throughout the whole development cycle (planning, implementation, testing, release, maintenance) following modern software development practices and are using AI expert assistance in all stages of your work.

• You are comfortable working with MCPs, REST APIs and other modern data science programmatic interfaces.

• You have abundant experience in managing FAIR data as well as tracking data lineage, ensuring data quality and improving data discovery.

• You are able to break down large problems into smaller software components and can develop them independently or as part of a large team.

• You are comfortable working both independently and collaboratively, and with handling several concurrent, fast-paced projects.

• Experience with Bioconductor and the Tidyverse ecosystem, as well as RMarkdown / Quarto, and Shiny and Plumber deployment, are beneficial.

• Experience with Python technologies (e.g. Pandas, Polars, Streamlit, FastAPI) is a plus as many of our stakeholders and systems are bilingual (R/python).

• Prior experience in a life science or drug development environment is beneficial.

What to expect from us

• A highly collaborative and dynamic research environment where we aim to advance the rate of scientific discovery using purposefully built solutions.

• 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.

Onsite presence, on our South San Francisco campus, is expected for at least 3 days a week.

Relocation benefits are not available for this job posting.

The expected salary range for this position, based on the primary location of South San Francisco, is $142,500 - $264,700 of hiring range.  Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.  A discretionary annual bonus may be available based on individual and Company performance.  This position also qualifies for the benefits detailed at the link provided below.

Benefits

#LI-JD1

#ComputationCoE

#tech4lifeComputationalScience 

#tech4lifeAI

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

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