THE POSITION

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
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 integrated research solutions. 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 (BER with GUPRIs), shared ontologies, and interoperable APIs.
As a Principal Product Leader for Integrated Research Solutions, you will work with senior scientific leadership across In Vivo, In Vitro and Cell Therapy research contributing to a coherent, end-to-end product experience across these areas. Your mandate is to translate scientific strategy into an actionable, outcomes-driven product roadmap that connects study design entity selection/registration protocol execution data acquisition/processing insights, reducing friction at every hand-off. You will partner with technical capability leaders and adjacent product leaders to influence functional and product roadmaps to align with your strategy. Integrated Research Solutions matter because they turn the research toolchain into a coherent, end-to-end operating system—linking study design, entity registration, protocol execution, data processing, and insights. By standardizing identifiers, metadata, and provenance at every step, they reduce hand-offs and rework, improve “first-time-right” execution, and make results reproducible and reusable across projects and modalities. This foundation accelerates learning cycles, unlocks automation and AI/ML at scale, and increases decision velocity for scientists and leaders. You will partner deeply with scientists, lab managers and operations, and automation specialists to understand hypotheses, constraints, and throughput needs; and with fellow product managers, engineering, data, and UX to design workflows that “start with the science.”
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.

KEY ACCOUNTABILITIES

• Define vision, strategy, and multi-year roadmap for the integrated research products aligned to research priorities and portfolio needs.
• Deliver integrated, research-centric workflows that connect study design, protocol execution, sample/material lifecycle, assay outputs, and insights—with clear provenance, access controls, and auditability.
• Drive platform interoperability using API-first, event-driven, ontology-aligned patterns; ensure seamless integration with ELN/LIMS, lab automation, instrumentation, and data platforms, and consistent use of GUPRIs and master data.
• Translate scientific needs into product outcomes through continuous discovery with PIs, lab scientists, assay owners, and operations; convert use cases into prioritized epics with explicit success criteria.
• Sequence high-value deliveries (pilots scaled adoption): balance foundational capabilities with quick wins; manage dependencies across adjacent product families and shared services.
• 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.
• Develop talent and culture: mentor other product managers in the domain, foster scientific empathy and product excellence, and promote a culture of experimentation, usability, and continuous improvement.

THE IDEAL CANDIDATE WILL SATISFY MANY OF THE FOLLOWING REQUIREMENTS:

• 10+ 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.
• Deep literacy in research workflows and lab informatics—how hypotheses become protocols, how samples/materials flow through ELN/LIMS/automation, how assay outputs turn into analysis-ready data—and how registries/master data (e.g., entity identifiers, controlled vocabularies) underpin reproducibility.
• Strong systems and data acumen: API-first and event-driven integration patterns, data modeling and ontologies, lineage/provenance, access control models (project-/study-based), auditability, and security/privacy-by-design.
• Track record delivering measurable outcomes (cycle-time reduction, first-time-right, reuse of entities/datasets, request-to-start SLAs) and instrumenting products with telemetry for evidence-based iteration.
• 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.
• Demonstrated capability to manage migrations from legacy tools (data cleansing, schema mapping, cutover, coexistence, decommissioning) with minimal disruption to active studies.
• 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 master data management, FAIR data practices, and governance operating models (data stewardship, model change control, metadata quality).
• Familiarity with lab automation ecosystems and instrument/data integration across key assay families (e.g., sequencing/omics, high-content imaging, flow cytometry, bioanalytical/PK/PD).
• Exposure to AI/ML enablement in research (feature stores, harmonized identifiers, training-set curation, model reproducibility) and to privacy/consent/IP constraints in preclinical and human-sourced data.
  The expected salary range for this position based on the primary location of California is $170,200 and $316,000. 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
  Relocation benefits are available for this posting.
  

  ComputationCoE

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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Please refer the Job description for details