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AI Lead, Discovery and Development

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: AstraZeneca
Full Time position
Listed on 2026-02-15
Job specializations:
  • IT/Tech
    AI Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Overview

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.

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.
  • Ownership & Delivery
    :
    Act as the product owner for AI solutions (e.g., target , 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.
  • 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.
Qualifications & 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.…
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