AI Science Innovation Strategy Lead

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Job Description We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation.

If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real.
** About the team
** AI Strategy & Innovation (AISI) sits at the centre of AstraZeneca's R&D AI transformation. Our remit is to transform pipeline outcomes across discovery, translational science, biomarkers and clinical development. AISI is organised around an AI Centre of Excellence, an AI Frontier research function, an Operations spine, and a Strategy group.

This role sits in Strategy. We drive the strategy that shapes the frontier: setting direction across the four scientific pillars, brokering external partnerships, running competitive intelligence, and building R&D's AI literacy. The work moves the portfolio.
** Role summary
** This role works at the intersection of business, science, and AI. You find where AI can solve real business problems and shape the right solution given the science and the data.

You own the strategy with the science and engineering teams. You go deep on the area, work out what data and AI solutions exist, decide the plan, and drive execution.

Our principle: you cannot own a strategy you do not understand. The facts, constraints and opportunities have to be yours before any plan is worth the paper. This role demands serious learning agility and a default to collaboration. Not authoring from a distance.

The bar is high. We need someone who can:
* Sit with a senior R&D scientific leader and understand the disease, asset and decision in front of them.
* Hold their own with AI engineers on foundation models, generative chemistry and agentic systems.
* Translate both into a sequenced AI bet that gets funded and shipped.
* Most strong candidates clear one. Some clear two. We are hiring for the few who clear all three. Many stakeholders are new to modern AI; bringing them along without dumbing down or overselling is the hard part.
** What you will own**
* ** Read the business and the science.
** Cover an area deeply enough that scientific leaders treat you as a peer. Spot the AI bets that move pipeline decisions, not the ones that look clever in a deck.
* ** Shape the solution before delivery starts.
** Survey what exists internally and externally. Decide what to build, buy or partner for. Pressure-test the data. Define the plan.
* ** Bring stakeholders along.
** Turn curiosity into committed sponsorship.
* ** Set strategy and run partnerships.
** Co-author the rolling AISI strategy across the four scientific pillars. Run diligence and deal-shaping with external partners; hand them over so AISI can execute.
* ** Tell the story.
** Narratives, decks and investment cases for AISI, R&D leadership and external audiences.
** What you bring
** Essential* Advanced degree in a quantitative or life-sciences discipline. PhD preferred.
* 5+ years across AI/ML and / or life sciences, with time owning strategy, capability or partnership decisions.
* Working fluency in modern AI/ML, foundation models and agentic systems. Enough to set direction and pressure-test partner claims.
* Experience translating AI into drug discovery, translational science, biomarkers, clinical development, regulatory or RWD, with concrete impact.
* Learning agility. You pick up a new disease area, modality or AI capability fast enough to lead the conversation inside three months. References will back this up.
* A default to collaboration. You build understanding by sitting with the people who hold the knowledge.
* Track record of bringing AI-nascent stakeholders along without patronising them.
* Sharp opportunity-spotting. You see the AI bet that creates outsized impact, not just the novel one.
* Matrixed, global organisation, no direct reports. You influence through clarity and momentum.

Desirable
* Time inside a pharma R&D AI function, AI-native biotech or similar.
* Familiarity with foundation models for biology and chemistry.
* Working knowledge of GxP, AI/ML regulatory expectations and responsible-AI frameworks.
** Why this role
** One of the highest-leverage seats in AZ's R&D transformation. Get this right and AZ ships better medicines, sooner.

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…