Director, AI & Data Partner Evaluation

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. This role sits at the intersection of AstraZeneca's Clinical Intelligence and RWE teams and the rapidly evolving external ecosystem of AI/ML platform companies, foundation model developers, multimodal analytics partners, and real-world data providers. The Data & AI Partnerships Lead will ensure that therapeutic area teams across Oncology (Lung/HNSCC, Women's Cancer, GI/GU, Haematology) and Biopharmaceuticals (CVRM, Respiratory, Immunology, Infectious Disease) can access, evaluate, and mobilize the right external capabilities — whether those are foundation models, computational platforms, agentic AI tools, or datasets — to power evidence generation, multimodal analytics, and AI-enabled clinical decision-making. The successful candidate will be a "T-shaped" technical operator — deep in AI/ML and computational partner evaluation, with sufficient breadth in real-world data to initiate and frame data assessments before handing off to TA RWE experts for deep validation. This is not a traditional business development role. In a typical week, this person might be: - Evaluating a multimodal foundation model partner's approach to integrating imaging, genomic, and clinical data for patient stratification in lung cancer - Assessing whether an agentic AI platform's orchestration capabilities are compatible with the team's infrastructure - Initiating a fit-for-purpose review of a new molecular data provider — scoping the key questions, running an initial completeness check, and then handing the detailed variable-level assessment to the Lung or GI/GU RWE Strategy Lead for domain-specific validation - Briefing senior stakeholders on a build-vs-license recommendation for a clinical trial simulation capability The right candidate will build their network through hands-on technical collaboration with AI and data partners and will be as comfortable interrogating a model's training methodology and validation evidence as they are framing a data quality question for a TA expert to resolve. **Role Scope** - **Technical Data Assessment:** Hands-on evaluation of external datasets against specific evidence questions — assessing volume, completeness, representativeness, variable availability, linkage capability, latency, coding standards, and regulatory acceptability. - **Data Partner Scouting & Network:** Maintain and expand a curated network of RWD, genomic, imaging, claims, EHR, registry, and digital health data providers relevant to Oncology and Biopharmaceuticals evidence needs. - **TA Evidence Alignment:** Partner with RWE Strategy Leads, Multimodal Analytics Leads, and Data Scientists across TAs to translate evidence gaps into data sourcing requirements. - **Partnership Lifecycle:** Own end-to-end data partnership management from scouting and pilot evaluation through contracting, onboarding, performance governance, renewal, and expansion aligned to the needs of the business. - **Cross-TA Data Strategy:** Identify opportunities to leverage a single data partnership across multiple therapeutic areas, maximizing value and reducing duplication. - **Regulatory & Compliance Alignment:** Ensure all proposed data partnerships meet privacy, ethical governance, and regulatory-grade evidence standards (EMA RW-DQF, FDA…