Scientific Digital Product Lead, Assay Workflows

Description

The company's Computational Sciences Center of Excellence uses data and AI to help scientists in Research and Early Development at Genentech (gRED) and Pharma (pRED) build better medicines faster.

The Data and Digital Catalysts team in that centre works with scientific groups to build the computing and data systems that support discovery and faster, data-driven decisions.

This role sits in the Assay Workflows domain and reports to its Domain Head. You will turn complex lab workflows into scalable, automated, AI-enabled platforms that serve experimental scientists and AI/ML research teams.

Required: a PhD or Master's in life sciences, computer science or a related field, plus 3+ years of relevant professional experience in drug discovery with a focus on data and digital work.

Responsibilities

• Set and update the product family strategy for Assay Workflows, in line with key strategic initiatives.
• Integrate applications and platforms into the data and digital ecosystem, and help consolidate or retire legacy systems to reduce technical debt.
• Turn scientists' needs into a roadmap: decide what to build and when, and why it matters, then guide cross-functional teams and manage stakeholder expectations.
• Work with engineering and data experts to build assay data workflows with scalable automation and modular design, so preclinical data yields faster, higher-quality insights.
• Run business analysis and product and programme or project management, prioritise work, manage budgets and oversee external contractors.
• Anticipate emerging technologies and methods and build them into the roadmap.
• Build trusted internal and external partnerships and work well with teams across the globe.
• Help across the domain beyond your own specialty when needed.

Requirements

• Deep knowledge of preclinical R&D, including assay workflows, preclinical imaging (digital pathology, biomedical imaging, optical screening, research microscopy) and complex in vitro models.
• Python or similar coding skills are a strong plus, and experience building workflows with AI-assisted coding is an advantage.
• Strong at both long-term strategy and hands-on delivery, and comfortable with ambiguous or changing situations.
• Proven record leading large cross-functional projects with many teams and stakeholders. Experience in platform strategy, advanced product management, business analysis and change management is valued, and prior drug discovery work is strongly preferred.
• Able to work with complex organisations, explain things clearly to varied audiences, and break large transformation plans into incremental steps that show measurable progress.
• Forward-thinking and agile, with curiosity and a drive to bring new technologies and methods into assay workflows, prioritise value and keep improving.
• Quick to learn and keen to apply fast-moving AI methods across complex scientific fields.
• The ideal candidate meets many, though not necessarily all, of these requirements.

Conditions

Equal opportunity employer.