Senior Product Leader, Therapeutics Discovery

About the role

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.

The Computational Sciences Center of Excellence (CS CoE) brings together scientific, data and computational capabilities to support research and early development across Genentech (gRED) and Pharma (pRED). Within CS CoE, Data and Digital Catalysts (DDC) bridges the informatics and scientific communities to create solutions that power scientific discovery and accelerate decision-making.

Reporting to the Therapeutics Discovery Domain Head, you will own a defined subset of scientific informatics products that enable assay request, setup, execution and experimental data capture.

Your focus will be to make data and metadata capture an integral part of experimental work: establishing the required scientific context before data are generated, capturing it as early as possible, and preserving what actually happened during execution.

These products should support the original scientific purpose while making results interpretable, traceable and reusable for scientific analysis, decision-making and machine learning.

The remit spans therapeutic modalities, with an emphasis on adaptable workflows that can support all drug discovery modalities over time.

As an integral member of this dynamic team, you will be

• Product ownership and prioritization. Own the roadmap, prioritization and outcomes for assigned products within a product family. Contribute to family strategy and align delivery with scientific priorities, working with the Domain Head, product family leads and engineering partners.
• Assay setup and execution. Understand how scientists request, prepare and execute assays. Translate these workflows into practical product requirements that capture known experimental context during request and setup, minimize repeated entry, and update records with actual conditions, deviations and quality information as work proceeds.
• Scientific data and metadata capture. Partner with experimental scientists and computational users to define the data, identifiers, relationships and metadata needed to interpret and reuse results. Embed appropriate capture and validation into workflows, supporting scientific analysis and machine learning without making scientists reconstruct context after the experiment.
• Coordination with adjacent capabilities. Enable capture into existing laboratory information management systems (LIMS) or the shared data layer being built, in line with agreed architecture. Coordinate with instrument-capture and data-layer teams to keep experimental context linked to results.
• Requirements, delivery and adoption. Translate scientific needs into clear user stories, functional requirements and acceptance criteria. Work with engineering and scientific partners to evaluate usability, validate delivered capabilities and drive adoption. Develop reusable approaches while preserving meaningful differences across assays and modalities.
• Workflow quality and measurable outcomes. Within your product scope, prioritize improvements that reduce manual workarounds and strengthen workflow reliability and data quality. Define and track outcomes such as setup effort, metadata completeness and adoption. Partner with engineering and support teams on sustainable maintenance and transitions to replacement capabilities.

Who You Are

We welcome experienced product leaders with substantial drug discovery understanding and drug discovery scientists who have moved into informatics or digital solution delivery. Scientific credibility, practical product capabilities and ownership of outcomes are essential; prior leadership of a broad product family is not required.

• Education and relevant experience. A bachelor's or advanced degree in a relevant scientific or technical discipline, with experience delivering impactful informatics solutions in biotechnology, pharmaceuticals or drug discovery. Typical experience for this role is a PhD plus 1–3 years, a master's degree plus 3–5 years, or a bachelor's degree plus 4–7 years.
• Drug discovery understanding. Substantial understanding of the drug discovery and research context, including how assays inform scientific decisions and how experimental conditions affect interpretation. Credible experience working with discovery scientists is essential; expertise across every modality is not.
• Product and delivery capability. Experience translating scientific problems into useful informatics solutions, gained through product management, business analysis, scientific informatics or related work. Demonstrated ability to prioritize needs, define requirements and take ownership of delivery and outcomes within a defined scope.
• Scientific data fluency. Understanding of experimental data and metadata, their relationships, and the context needed for scientific interpretation and reuse. Ability to work with scientific and technical partners to turn these needs into usable capture workflows.
• Collaboration and communication. Ability to build trusted relationships, lead through influence, and communicate scientific needs and product decisions clearly to scientists, engineers and leadership. A collaborative approach to solving problems across team boundaries.

Preferred Experience

• Hands-on assay development or execution experience is preferred, not required.
• Experience with assay request or execution systems, LIMS, or experimental data capture is valuable, as is experience applying product practices to scientific workflows.
• Machine learning model development is not a requirement.

Relocation benefits are not available for this posting.

Pay and benefits

The expected salary range for this position based on the primary location of California $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

• #ComputationCoE
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