The PositionAt Genentech Research & Early Development (gRED) we have initiated an exciting journey to bring together and further strengthen our computational talent and capabilities by forming a new, central organization - gRED Computational Sciences (gCS). gCS is on a mission to partner across the organization to realize the potential of data, technology and computational approaches that will revolutionize how targets and therapeutics are discovered and developed, ultimately enabling novel treatments for patients across the world.

We stand at the beginning of an exciting journey. The Computational Catalysts group within gCS is a diverse, curious and action-driven team at the intersection of computation, engineering and science with ambition to advance our technical excellence. The focus of the team is on partnering with the informatics and scientific communities to create a computational and data ecosystem that powers scientific discovery and accelerates decision making.

We aim to modernize our ability to acquire, store, link, share, find and analyze data across the organization through scalable and integrated solutions that truly make every data point count. We have partnered closely with our gRED colleagues to develop enhanced data capture, pipelines and processes to accelerate our ML efforts and impact.As a hands-on data/software engineer in the Computational Catalysts group, you will be responsible for collaborating with diverse groups in gRED including Drug Discovery scientists, machine learning engineers, and Computational Catalysts informatics teams to support the Lab in the Loop approach which utilizes AI/ML for antibody identification, optimization and de novo design.

This role requires strong data engineering technical skills including familiarity with a variety of database types and models. You have the desire and ability to learn and understand the purpose and details of data models used in scientific systems spanning diverse domains, including: large molecule registration, laboratory information systems for assay data acquisition and other relevant experimental data. Key Accountabilities:Learn and understand the data models for key systems supporting our science and scientistsGeneral data wrangling including: ensuring data quality, data coverage, and acting as a resource for technical questions about scientific system data modelsBuild, maintain and evolve the self-service data platform and associated data productsProvide curated views of data as requiredWork with the Protein Sciences and machine learning teams to provide data from operational and LIMS systems for drug discovery efforts, enabling the lab in the loop Deliver on the goal of bringing diverse sets of data together to support a wide range of activities such as AI/ML, search, reporting, and analyticsSuccessful candidates will meet many of the following requirements: BS degree or higher in Computer Science, Data Science, mathematics, engineering or scientific disciplineAt least 4 years of experience in designing and implementing ETL, data pipelines, data warehousing, or other data engineering solutionsExperience working in a life sciences or biopharmaceutical environment such as early-stage research, drug discovery, or other biological sciences discipline is preferredFamiliarity with diverse database types including Oracle, Postgres, MongoDB, etc.

is preferredKnowledge of established programming languages such as Python, Java, and RFamiliarity with data engineering patterns and pipeline tools and processes including: SQL vs NoSQL, CQRS, ETL, Data Warehousing, data warehouse/management platforms (eg Snowflake), Data Lakes, Apache Kafka, Event Streaming, Data Mesh, Elasticsearch/ELK, GraphQL, and DataOpsExperience with software development on at least one commonly used public cloud platform (eg AWS, GCP, Azure)Demonstrated success working independently on initiatives of high complexity, uncertainty, and risk with minimal guidance and directionAble to present your work, both verbally and in writing, to diverse audiences including scientific stakeholders, technical teams, as well as research leadership*Relocation benefits are available for this job posting*The expected salary range for this position based on the primary location of South San Francisco, CA is $132,400.00 - $245,800.00 USD Annual. 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. Benefitsis an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.

Job SummaryJob number: 202312-128221Date posted : 2023-12-18Profession: Data Science & AI/MLEmployment type: Full time.