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 (CS 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 Data and Digital Catalysts (DDC)  department within the CS CoE  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.  Reporting to the Domain Head for Lab Workflows & Data, this Senior Product Leader will play a key role in defining and executing the strategy for a family of products that are critical for drug discovery research. 

The Lab Workflows & Data domain provides the end-to-end digital backbone for research design, experiment management, assay data & insights, and Lab Workflows & Data . It spans hypothesis and study design (protocol authoring, approvals, ELN linkage), experiment orchestration (intake, scheduling, LIMS/LES execution), and the full sample/material lifecycle with automation, provenance, and chain-of-custody. It delivers assay data & insights capabilities—standardized ingestion, processing/secondary–tertiary pipelines, QC, lineage, harmonization, and analytics-ready datasets—underpinned by governed research master data, shared ontologies, and interoperable APIs. 

As a Senior Scientific Product Leader for Lab Workflows & Data, you will lead an integrated product strategy for lab workflows, research data, and AI/ML enablement. Working with senior scientific leadership across Research and Development, you will translate scientific priorities into an outcomes-driven roadmap spanning study design, entity selection and registration, protocol execution, data acquisition and processing, and insights.

You will make high-quality, governed, reproducible, and reusable data a core product outcome—not simply an output of workflow execution. Your roadmap will address the identifiers, metadata, provenance, harmonization, and data quality needed to support scientific analysis, training-set curation, and model reproducibility.

Partnering with scientists, lab managers and operations, automation specialists, technical capability leaders, and product, engineering, data/AI, and UX teams, you will translate research needs into prioritized workflow, data, and AI/ML capabilities. You will balance foundational investments with high-value deliveries, establish explicit success criteria, and guide capabilities from pilots to scaled adoption—reducing hand-offs and rework, accelerating learning cycles, and improving scientific decision making.

This is an exciting opportunity to significantly impact and accelerate discovering diverse therapeutics that fundamentally make patients’ lives better.  You will have the opportunity to work closely with Genentech’s top tier scientists and drug discovery experts.

The Opportunity:

• Own an integrated workflow, data, and AI product strategy. Define the vision, strategy, and multi-year roadmap for lab workflows, research data, and AI/ML-enabling capabilities, aligned to scientific priorities and portfolio needs. Make foundational data investments and their contribution to research outcomes explicit in roadmap decisions.
• Own research-data capabilities as product outcomes. Deliver integrated workflows connecting study design, protocol execution, the sample/material lifecycle, assay outputs, and insights. Define product requirements for standardized ingestion, processing, QC, metadata, lineage/provenance, and harmonization so that datasets are reproducible, reusable, and suitable for scientific analysis and AI/ML.
• Lead AI product discovery and prioritization. Through continuous discovery with PIs, lab scientists, assay owners, and operations, identify and prioritize opportunities for AI/ML-enabled research capabilities. Partner with data/AI and engineering teams to translate these opportunities into product requirements, data-readiness requirements, prioritized epics, and explicit success criteria.
• Drive governed platform and data interoperability. Use API-first, event-driven, ontology-aligned patterns to connect ELN/LIMS, lab automation, instrumentation, and data platforms. Ensure consistent use of GUPRIs, master data, and shared ontologies, with clear provenance, access controls, and auditability.
• Lead change and adoption by establishing communication plans, training curricula, role-based onboarding, super-user networks, and feedback loops.
• Orchestrate cross-functional delivery (product, engineering, data/AI, UX, QA/CSV, security, privacy, procurement/vendors); remove blockers, manage risks, and maintain a durable delivery cadence.
  

Who You Are:

In hiring new employees, we look for people who are inspired by our mission and can thrive with the collaborative, thorough, and entrepreneurial spirit of our company culture. Because we know that employees are essential to our success in bringing novel medicines to patients, we are dedicated to remaining an extraordinary place to work and to providing employees with programs, services, and benefits that allow them to bring the best to the organization and to their personal lives.

The ideal candidate will satisfy many of the following requirements:

• 5+ years of product leadership in life-sciences R&D (biotech/pharma, CRO, or research tech), including end-to-end ownership of a complex product area serving scientists and lab operations.
• Demonstrated AI product leadership in scientific research. Experience translating scientific needs into prioritized AI/ML product capabilities, defining success criteria, and partnering with data/AI and engineering teams to move from use-case discovery through pilots and scaled adoption. Able to connect AI product priorities to scientific outcomes and the data foundations required to achieve them.
• Deep research-data expertise. Strong understanding of how assay outputs become high-quality, analysis-ready, and reusable datasets through ingestion, processing, QC, harmonization, and lineage/provenance. Able to translate requirements for training-set curation, harmonized identifiers, and model reproducibility into actionable product priorities.
• Strong systems and data-governance acumen. Experience with API-first and event-driven integration, data modeling and ontologies, master data management, FAIR data practices, metadata quality, and data stewardship. Understand how project- and study-based access controls, auditability, and security/privacy-by-design support governed data sharing and reuse.
• Track record of delivering measurable scientific and data outcomes, including cycle-time reduction, first-time-right execution, improved data and metadata quality, and increased reuse of entities and datasets. Experience instrumenting products with telemetry and using evidence to guide prioritization, iteration, and adoption.
• Skilled at stakeholder leadership across PIs, lab managers, assay owners, data/AI teams, product/engineering, and executive sponsors; excellent written and verbal communication tailored to scientific and executive audiences.
• Comfortable operating in a matrixed, global organization; adept at change management, roadmap sequencing, and risk management for multi-team deliveries.

Preferred Qualifications:

• Advanced degree in a life-science discipline (PhD, PharmD, MD, MS) or comparable hands-on lab experience that enables fluent conversations with researchers and scientific staff.
• Experience with lab automation ecosystems and instrument/data integration across key assay families (e.g., sequencing/omics, high-content imaging, flow cytometry, bioanalytical/PK/PD).

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 California is $126,100 - $234,100.  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

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