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This role will partner closely with R&D teams to translate scientific challenges into actionable AI opportunities, accelerate pipeline productivity, enable AI-driven solutions that accelerate innovation, enhance scientific rigor, and advance transformative medicines for patients with rare diseases. You will lead the design, development, and adoption of advanced AI/ML capabilities that elevate target discovery, optimize trial design and execution, strengthen data\u2011driven decision making, and unlock new scientific insights across the R&D lifecycle. This role blends deep technical expertise with strong product thinking, scientific acumen, and exceptional stakeholder leadership. You will be responsible for: AI Strategy & Portfolio: Identify and prioritize business aligned AI opportunities and define the multi-year AI strategy and roadmap. Govern the portfolio from proof of concept through validation to scaled products, with clear stage gates, success metrics, and value tracking.\u2011aligned AI opportunities \u2011of\u2011concept through validation to scaled products, with clear stage gates, success metrics, and value tracking. Ownership & Delivery: Act as the product owner for AI solutions (e.g., target ID, compound optimization, translational and clinical decision support). Set problem statements, adoption thresholds, and benefits realization plans; oversee delivery with internal teams and partners. Business Interface & Partnerships: Serve as the primary interface between R&D teams, data scientists, and external AI partners. Translate scientific and operational needs into AI solutions. Evaluate buy\u2011build\u2011partner options and manage vendors/consortia. Workflow Integration & Change: Lead the integration of AI into business workflows, data systems, and SOPs. Drive change management and adoption programs, including stakeholder engagement, training, communications, super\u2011user networks, feedback loops, and human\u2011in\u2011the\u2011loop controls. Data & Platforms: Partner with the Head of Data and Tech teams to enable access to high-quality, well governed research and clinical data, promote FAIR principles, and influence platform architecture and MLOps/LLMOps considerations to scale AI responsibly.\u2011quality, well\u2011governed research and clinical data, promote FAIR principles, and influence platform architecture and Governance, GxP & Responsible AI: Ensure AI solutions meet GxP, data integrity, privacy, and audit requirements. Establish practices for model validation, bias/robustness testing, explainability, documentation, model monitoring, performance SLAs, and inspection readiness. Impact & Communication: Define OKRs/KPIs tied to R&D outcomes (e.g., hit/lead success rates, cycle\u2011time reduction, protocol optimization, enrollment speed, cost avoidance, risk detection). Track and communicate progress, impact, and value to R&D and executive leadership with clear narratives and evidence. Talent & Culture: Build and nurture a cross\u2011functional network of super\u2011users and AI champions; set standards and best practices. Foster a culture of scientific rigor, product thinking, innovation, and measurable impact; promote agile ways of working across Alexion. You will need to have: Education: Advanced degree preferred (MS/PhD in life sciences or quantitative fields; or MBA) with strong biopharma R&D exposure and meaningful AI familiarity (coursework, certifications, executive programs, or applied initiatives). Experience: 10+ years in biopharma/biotech R&D or adjacent life sciences functions, with 5+ years leading cross\u2011functional, technology\u2011enabled portfolios and driving business outcomes. Demonstrated success sponsoring or directing AI initiatives from concept to scaled adoption, including vendor and partner management. Business Domain Expertise: Deep understanding of the end\u2011to\u2011end R&D value chain. Able to translate scientific and operational needs into AI\u2011enabled business solutions. Product and Portfolio Leadership: Proven ability to define roadmaps, prioritize portfolios, manage budgets, and deliver measurable impact. Stakeholder Management: Credible partner to senior scientific and business leaders; skilled at influencing without authority, facilitating decisions, and aligning cross\u2011functional teams around clear outcomes. Comfortable serving as the owner for AI solutions and representing needs to data science and engineering teams. Workflow Integration & Change: Experience integrating new capabilities into business workflows; adept at change management, adoption, and benefits realization. Data & Governance Fluency: Knowledge of FAIR principles, clinical and research data landscapes, and vendor/partnership management. Understand data readiness for AI, feature/data access controls, and lineage/traceability requirements for model auditability. Regulatory & Compliance: Working knowledge of GxP, data integrity, privacy (GDPR/CCPA/HIPAA), audit requirements, and documentation standards in regulated workflows. Familiarity with responsible AI principles, model risk management, and documentation needed for validation in preclinical and clinical contexts. Technical Fluency (non\u2011coding): Comfortable engaging with AI/ML concepts such as predictive modeling, NLP/LLMs. Able to assess value, risk, and feasibility; understand AI and platform considerations to make informed decisions and ask the right questions without needing to code or build models. Communication & Storytelling: Exceptional ability to simplify AI concepts for scientific and business audiences; craft outcome\u2011focused narratives and adoption cases; report progress, impact, and value to R&D and executive leadership with clear evidence and trade\u2011offs. We would prefer for you to have: Rare disease R&D exposure and strategies for small\u2011sample learning and external data augmentation. Experience acting as business product owner for AI solutions, driving adoption and measurable outcomes. Portfolio financial acumen (investment cases, ROI) and partnership governance (buy\u2011build\u2011partner, success measures, IP/publications stance). In-Office/Hybrid Statement: When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work on average a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world. Compensation and other factors: The annual base pay (or hourly rate of compensation) for this position ranges from $203 213,60 - $304 820,40. Our positions offer eligibility for various incentives\u2014an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans. At AstraZeneca's Alexion division for Rare Diseases you will find an environment where work is more than just a job\u2014it's a mission. Our closeness to patients brings us closer to our work and each other. With a rapidly growing portfolio in a nimble biotech atmosphere supported by global resources, tailored development programs are crafted to improve your skills. These programs encourage a deep understanding of our patients' journeys. Here diversity is valued; inclusion is championed; innovation is celebrated; all while making a profound impact on patients' lives. Ready to make a difference? Apply now! 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