Data Innovation Specialist - AI & Real-World Data

Genentech; South San Francisco (CA); On-site; USD 97,900 - 181,700; Full time

Job summary

Genentech is seeking a Data Innovation Specialist (RWD) to identify, prototype, and scale novel data methods across real-world, clinical, and operational datasets. You will report to the Data Innovation Head and work with scientists, engineers, and product teams in a collaborative, innovation-focused environment.

The role emphasizes experimentation and continuous learning, with responsibilities spanning AI development, data engineering, and knowledge graph integrations in a multi-modal setting.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Informatics, Life Sciences, or a related field.
• 2–4 years of data-related or innovation projects, or an advanced degree with 0–2 years experience.
• Basic familiarity with Python or R and Git.
• Ability to document technical findings clearly.
• Demonstrated independent thinking and decision-making.
• Strong strategic agility, problem-solving, and cross-cultural collaboration.

Responsibilities

• Prototype, validate, and scale advanced AI capabilities with multi-agent development.
• Design robust data pipelines for unstructured, multi-modal data integration.
• Explore knowledge graphs and automated agent workflows in a multi-modal setting.
• Collaborate with scientists, engineers, and product teams to pilot data innovations.
• Create low-/no-code analytics platforms to democratize data access.
• Mentor peers on new data modalities and architectures, ensuring compliant practices.

Skills

Data science basics

Python or R

Git/VCS

Communication

Independent thinking

Collaboration

Problem solving

Education

Bachelor/Master in Data Science or related

Tools

AI frameworks

Knowledge graphs

Job description

Genentech is seeking a Data Innovation Specialist (RWD) to identify, prototype, and scale novel data methods across real-world, clinical, and operational datasets. You will report to the Data Innovation Head and work with scientists, engineers, and product teams in a collaborative, innovation-focused environment.

The role emphasizes experimentation and continuous learning, with responsibilities spanning AI development, data engineering, and knowledge graph integrations in a multi-modal setting.