DUTIES & RESPONSIBILITES
1. Product Vision, Strategy & Roadmap
- Own the product vision, strategy and multi-year roadmap for a portfolio of scientific digital, data and AI products, aligned with R&D scientific strategy and the China IT and global R&D IT strategy
- Map products and capabilities to the Clinical development lifecycle (Phase III, regulatory submission and lifecycle management) to find where digital and AI can remove bottlenecks and speed up decisions
- Define the target technology stack for the domain (e.g. scientific computing/HPC and cloud, omics and biomarker data pipelines, translational and clinical data platforms, analytics and ML/AI tooling) and make build/buy/reuse decisions aligned with enterprise architecture
- Turn long-term scientific plans into a prioritised, outcome-based roadmap with clear OKRs and measurable value hypotheses
2. Business Partnership & Scientific Domain Leadership
- Act as the single accountable product partner for supported scientific teams, building trusted relationships from working level to senior scientific leadership
- Develop a deep understanding of scientific workflows and data flows (e.g. NGS/multi-omics analysis, biomarker strategy, PK/PD and quantitative modelling, clinical data review and statistical analysis) and use product discovery and user research to uncover high-value opportunities
- Shape demand into business cases, value hypotheses and investment proposals; manage stakeholder expectations and trade-offs transparently
- Represent China R&D needs in global product forums, so that local requirements (e.g. NMPA submissions, China data regulations) are built into global products
3. Product Backlog & Agile Delivery
- Own and prioritise the product backlog; define epics, user stories and acceptance criteria, and make timely scope and release decisions that maximise value
- Lead cross-functional Agile squads (engineering, data, UX, vendors/OSPs) and drive iterative delivery from MVP to scale
- Coordinate dependencies with platform, data, infrastructure, security and global product teams; manage risks, issues and release readiness
- Drive user adoption, training and change management so products become part of day-to-day scientific work
4. Data & AI Innovation
- Identify, assess and prioritise AI/ML and GenAI use cases (e.g. LLM-based literature and knowledge mining, agentic workflows for scientific data analysis, AI-assisted biomarker discovery, support for protocol and document authoring)
- Take AI use cases from proof of concept to production, covering data readiness, model evaluation, human-in-the-loop design and MLOps/LLMOps
- Champion FAIR data, data quality and reusable data products so scientific data can power analytics and AI across development phases
- Ensure AI solutions follow AstraZeneca’s responsible and ethical AI principles and AI governance processes
5. Value, Budget & Vendor Management
- Own the product portfolio budget: annual planning, Mid-Term Plan (MTP) inputs, forecasting, actual-vs-plan tracking and variance analysis
- Track product KPIs and value realisation (e.g. cycle-time reduction, adoption, cost avoidance, decision quality) and report outcomes to IT and business leadership
- Apply Cloud FinOps discipline to optimise cloud consumption, run cost and licence spend
- Manage vendor and OSP relationships for the portfolio, including SOWs, SLAs/KPIs and performance reviews
6. Compliance, Quality & Capability Building
- Ensure products meet GxP and computer system validation/assurance requirements (e.g. GAMP 5, 21 CFR Part 11, EU Annex 11) where applicable, together with information security and data privacy standards
- Ensure compliance with China regulations on personal information, data security and human genetic resources, including cross-border data transfer, in partnership with Legal and Privacy
- Coach and mentor Associate Product Owners and business analysts, and promote product management and Agile best practice across R&D IT
JOB REQUIREMENTS & COMPETENCIES
Job requirements
Academic / Professional qualification
- Bachelor’s degree in Bioinformatics, Computational Biology, Life Sciences, Data Science, Computer Science, Information Technology or a related field (essential)
Technical / skill training
- Product ownership certification (e.g. CSPO, PSPO, SAFe POPM) preferred
- Cloud (e.g. AWS) and/or AI/ML training; certifications such as PMP, CBAP or TOGAF are a plus
Working experience
- 8+ years in pharma/biotech R&D IT, scientific informatics or a related area, including 3+ years as product owner, product manager or IT business partner
Essential
- Pharma or biotech R&D experience with a working understanding of the drug development lifecycle (preclinical, Phase I–III, regulatory submission, lifecycle management) and how data and decisions flow between phases
- Strong domain understanding in at least one of bioinformatics, data science or development science (e.g. translational/precision medicine, biomarkers, clinical pharmacology, quantitative sciences)
- Proven track record owning product vision, roadmap and backlog, and delivering digital products with Agile methods
- Hands-on experience taking AI/ML or GenAI solutions from concept to production, with a clear view of their value, limitations and risks
- Solid knowledge of cloud, data platforms, scientific computing and modern data and analytics architecture
- Experience owning product budgets and managing vendors
- Working knowledge of GxP, CSV/CSA and data privacy requirements in a regulated environment
- Excellent communication and influencing skills with both scientists and technologists; high autonomy and able to manage multiple products at once
Desirable
- Experience supporting clinical development
- Hands-on familiarity with scientific computing environments (HPC, cloud-based pipelines, workflow tools such as Nextflow) and common bioinformatics/data science tools (R, Python, notebooks)
- Familiarity with clinical data standards (CDISC SDTM/ADaM) and the clinical data ecosystem (EDC, CTMS, statistical computing environments)
- Experience with NMPA requirements, multi-regional clinical trials and China data regulations (PIPL, Data Security Law, human genetic resources)
- Experience in global, matrixed organisations
Language ability
- Fluent English and Mandarin Chinese, written and spoken; able to present complex topics to senior international audiences
Computer literacy
- Proficient with Agile and product tools (e.g. Jira, Confluence, Miro), MS Office and BI tools (e.g. Power BI)
- Practical, everyday use of GenAI tools; working knowledge of Python, R or SQL is a plus
Others
Key competencies:
- Product mindset and outcome orientation
- Scientific and business acumen in pharma R&D
- Strategic thinking and clear prioritisation
- Stakeholder management and influencing without authority
- Curiosity and continuous learning in AI and digital
- Ownership, autonomy and results orientation
- Lives AstraZeneca’s values
Date Posted
29-10月-2026
Closing Date
30-12月-2026
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.