GSK R&D and Digital & Tech are looking to leverage data, knowledge, and prediction to find new medicines, and the Onyx Research Data Tech organization is designed to deliver a step-change in this ability.
Requirements
- Experience defining product strategy for modern applications, including experience working closely with data scientists, ML engineers, and domain experts to shape model requirements, model evaluation frameworks, and end-to-end user workflows.
- Experience with AI/ML fundamentals, including understanding of model development lifecycles, data pipelines, feature engineering, and MLOps practices—paired with the ability to translate business needs into technical requirements.
- Experience integrating AI models into user-facing products, including UX workflows, decision-support tools, automation flows, or scientific applications used by R&D teams.
- Familiarity with modern ML and transformer-based architectures, with the ability to evaluate trade-offs between off-the-shelf models, open-source models, and domain-specific fine-tuned models depending on performance, regulatory, and data constraints.
- Experience developing products that analyze or surface complex, unstructured scientific data, including biomedical text, omics data, imaging, or knowledge graphs.
- Working knowledge of bioinformatics, computational biology, or cheminformatics, and a clear vision for how AI-driven applications can accelerate research workflows and scientific decision-making.
- Product experience shaping end-to-end ML-driven workflows, including feature pipelines, model serving, monitoring, human-in-the-loop review, and domain-specific UX requirements for scientific users.
Responsibilities
- Own and drive the product vision, roadmap, and adoption of the AI/ML Platform, delivering core capabilities for model training, fine-tuning, evaluation, deployment, monitoring, and lifecycle management.
- Define the strategic direction for foundational AI/ML tooling and ensure platform capabilities meet the needs of diverse R&D model development workflows and scientific applications.
- Conduct ongoing customer discovery with scientists and AI/ML practitioners to identify emerging needs and translate them into actionable product requirements.
- Lead technical product discussions with engineering and scientific leaders to clarify objectives and shape platform direction.
- Collaborate with stakeholders to define platform features, requirements, and success criteria aligned with scientific use cases and business goals.
- Drive agile product execution with engineering and program teams, owning prioritization, backlog management, and delivery of high-quality platform releases.
- Ensure seamless integration with the Data Platform to enable shared data standards and consistent data/model lifecycle management.
Other
- PhD + 2 years, Masters + 4 years, or Bachelors + 6 years
- 4+ years of experience in product management with a proven track record of delivering AI-powered applications (0-to-1 or scaled products) that solve concrete business or scientific problems in an enterprise or regulated environment.
- Ability to drive adoption, change management, and measurable business impact for AI solutions across diverse R&D user groups.
- Previous experience in life sciences or biopharma R&D is a strong plus.
- US employees are eligible for health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.
