# Senior AI Impact & Applied Innovation Specialist at AstraZeneca

AstraZeneca is hiring a Senior AI Impact & Applied Innovation Specialist in Cambridge, United Kingdom. Level rates it Builds AI ●●●●; you can [apply on AstraZeneca](https://jobsbylevel.com/go/03b6bf6a-0102-4378-8e40-a5c6df351ea4?utm_medium=ai-agent).

AI Level 4, AI centrality 87 out of 100. UK - Cambridge.

## Details

- Company: [AstraZeneca](https://jobsbylevel.com/companies/astrazeneca)
- AI level: AI Level 4 (score 87 out of 100)
- Location: UK - Cambridge
- Posted: October 28, 2026
- Apply: https://jobsbylevel.com/go/03b6bf6a-0102-4378-8e40-a5c6df351ea4?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-ai-impact-applied-innovation-specialist-at-astrazeneca-5e35e9

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## Description

Role: Senior AI Impact & Applied Innovation Specialist Location: Cambridge UK Salary: Competitive + Excellent Benefits Are you ready to translate AstraZeneca's frontier AI capabilities into concrete impact for the organisation? The Applied AI Research team, part of the AI Science Innovation (AISI) group within Enterprise AI (EAI), sits at the intersection of frontier AI research and oncology R&D, with a mission to ensure that advances in foundation models, agentic systems, and biological AI find their way to the problems where they will have the greatest impact on how we discover and develop medicines. As Senior AI Impact & Applied Innovation Specialist , Applied AI Research, you will be involved in both sides of that translation: identifying where frontier AI can address fundamental drug discovery questions for AstraZeneca, and orchestrating focused cross-departmental projects to answer them. You will maintain a structured view of AZ's highest-value AI science problems – mapping which questions most need answers, which frameworks are now mature enough to address them, and where AZ's unique data, biology, and portfolio create irreplaceable scientific advantage. You will also act as the scientific lead and orchestrator for delivering against those problems, assembling the right combination of expertise and resources and holding the scientific hypothesis through to a result that changes a decision. This is a role for someone familiar with key questions across the drug discovery pipeline, who can attend a frontier AI seminar and immediately see which ideas are applicable to areas from target identification to trial design, and who has the scientific conviction to advocate for a particular problem in the face of competing priorities. If you thrive at the intersection of machine learning and translational oncology and want to leave a direct mark on the scientific questions that shape AstraZeneca's pipeline, this role is for you. Typical Accountabilities AI Landscape & Opportunity Mapping: Maintain an interactive framework providing a structured, dynamic inventory of AZ's internal and external AI capabilities, including frontier models and platforms. Identify high-priority scientific questions—such as those in target discovery, combination therapy, tumor mapping, and trial design—where frontier AI can deliver significant value. Distinguish opportunities unique to AstraZeneca from those addressable with generic tools or public data. Scientific Evaluation Standards: Apply scientific expertise and evaluation standards to AI-driven frameworks designed to maintain a live, structured record of R&D goals and decision-making. Design and apply evaluation approaches for generative and agentic systems, including harnesses, benchmarks, trajectory-level metrics and validated LLM-as-judge methods, and run structured red-teaming (adversarial testing, failure-mode taxonomies, pre-release and continuous monitoring). Advise on and test where AI agents can responsibly automate steps in scientific, clinical and operational research processes, defining oversight points, acceptance criteria and comparison with the manual baseline. Forward-Deployed Embedding & Delivery: Translate scientific hypotheses into well-specified, time-bounded projects with pre-defined success criteria, with a clear path to integration and deployment; orchestrate the delivery of these projects Establish frameworks for quantifying impacts of AI projects and measuring impact for the business and implement these for active cross-functional projects. Stakeholder Communication & Leadership: Communicate AI science priorities, programmed status, and strategic recommendations to senior stakeholders across EAI, Oncology R&D and Biopharma R&D; act as the scientific bridge between AISI strategy and execution-layer teams, ensuring that frontier insight translates into actionable work and that delivery blockers are visible to leadership. Essential Requirements: Advanced degree (PhD preferred;

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