(Senior) AI Scientist - AI Alliance/Innovation

Key Responsibilities
•    Opportunity sourcing and due diligence: Proactively identify academic and industry partners; lead technical and scientific assessments, evaluate data readiness, integration feasibility, IP posture, and regulatory considerations; develop clear recommendations and business cases.
•    Pilot co-design and execution: Co-create and run time-bound pilots with partners and internal teams; define hypotheses, success metrics, datasets, guardrails, and delivery plans; ensure robust benchmarking against internal baselines and state-of-the-art.
•    Data and model integration: Coordinate data access, curation, and governance; align on interoperable formats and pipelines to integrate external models and outputs with AZ systems and workflows.
•    Translation to impact: Drive the adoption of successful pilots into discovery and engineering workflows; define scale-up plans, change management, training, and monitoring; ensure reproducibility, documentation, and compliance.
•    Cross-functional collaboration: Bridge computational and experimental domains—partner with wet lab scientists to guide experimental design and rapid data generation; align with bioinformatics, protein engineering, structural biology, data engineering, IT, Legal, and Procurement.
•    Alliance management: Negotiate and manage MOUs/PoCs/MSAs; establish joint roadmaps, operating cadences, and relationship health metrics; safeguard AZ interests on IP, data privacy, and security.
•    Thought leadership and visibility: Represent AZ in AI consortia and conferences; contribute to publications, patent filings, and strategic collaborations; amplify outcomes from pilots and partnerships.
•    Shanghai hub execution: Leverage China’s vibrant AI ecosystem; develop local partnerships; support bilingual communication and navigate region-specific regulatory and data considerations.

Required Qualifications
•    Master’s degree or equivalent experience in mathematics, physics, computer science, computational biology, bioinformatics, or related disciplines.
•    Hands-on experience applying machine learning/deep learning to biological sequences or structures (proteins, antibodies, peptides), including self-supervised and supervised methods.
•    Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) sufficient for technical due diligence, benchmarking, and pilot oversight.
•    Proven ability to work collaboratively in fast-paced, multidisciplinary, and cross-geographical environments; strong stakeholder management skills.
•    Clear and effective communication skills in English; Mandarin proficiency for partner engagement in China.

Preferred Qualifications
•    Experience running collaborative pilots or alliances with academia/startups/industry; familiarity with IP, licensing, and research agreements in partnership contexts.
•    Familiarity with large-scale cloud computing, modern data engineering, and interoperability standards relevant to integrating external AI solutions.
•    Publication record in AI, computational biology, or protein engineering; contributions to consortia or community standards are a plus.
•    Understanding of biologics drug discovery workflows and decision points, including data governance, GxP-adjacent practices, and model monitoring considerations.
•    Knowledge of state-of-the-art protein modeling, structure prediction, de novo design, and agentic AI approaches, with ability to assess partner capabilities rigorously.

Core Competencies
•    Scientific rigor with a translational mindset
•    AI/ML literacy and technical due diligence
•    Partnership building and alliance management
•    Program management and agile delivery
•    Data governance, ethics, and risk management
•    Clear written and verbal communication
•    Curiosity, adaptability, and bias to action

Success Metrics
•    Number, quality, and impact of sourced partnerships and executed pilots
•    Time-to-assessment and clarity of go/no-go decisions
•    Adoption of successful solutions into biologics workflows
•    Partner satisfaction and relationship health
•    External visibility (publications, talks, consortia contributions)

Working Arrangements
•    Shanghai-based with occasional domestic and international travel for partner engagement and internal collaboration.

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 authorisation and employment eligibility verification requirements.