AI Lead, Discovery and Development

AstraZeneca • Boston, MA

11d • Hybrid

About The Position

Alexion is seeking a visionary AI lead to shape and execute the AI strategy across our R&D organization, spanning early research, preclinical work, and clinical development. 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‑driven 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.

Requirements

• 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‑functional, technology‑enabled 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‑to-end R&D value chain. Able to translate scientific and operational needs into AI‑enabled 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‑functional 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‑coding): 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‑focused narratives and adoption cases; report progress, impact, and value to R&D and executive leadership with clear evidence and trade‑offs.

Nice To Haves

• Rare disease R&D exposure and strategies for small‑sample 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‑build‑partner, success measures, IP/publications stance).

Responsibilities

• 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.‑aligned AI opportunities ‑of‑concept 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‑build‑partner 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‑user networks, feedback loops, and human‑in‑the‑loop 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.‑quality, well‑governed 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‑time 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‑functional network of super‑users 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.

Benefits

• qualified retirement programs
• paid time off (i.e., vacation, holiday, and leaves)
• health, dental, and vision coverage in accordance with the terms of the applicable plans

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level