The role
From AstraZeneca's own posting.
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.
Our DS&AI Products team is the OBU's in-house engine for that work. We lead all aspects of the full lifecycle of AI-powered applications spanning predictive field triggers, patient-identification models, omnichannel next-best-action, KOL intelligence, and GenAI-powered field tools — and we ship products, not reports. Every capability we build must deliver measurable field adoption and commercial impact.
We are hiring a Director, DS&AI Products who will lead a multi-indication AI product portfolio end-to-end, serve as the strategic DS&AI business partner to OBU brand and medical leadership, and lead the responsible design, delivery, adoption, and impact measurement of AI solutions that drive commercial lift and better patient outcomes.
Role overview
This is a product ownership and program strategy role — not an analytics consulting role. You lead the full AI product lifecycle: problem definition, customer research, product requirements, AI development partnership, UX design alignment, deployment, change management, and post-launch impact measurement. You are the product owner and strategist for the AI capabilities powering Sales, Marketing, and Medical Affairs across your assigned OBU tumor areas, and the liaison US Oncology and the broader AstraZeneca Enterprise AI organization for customer engagement capability building.
You will be equally comfortable writing a product requirements document, reviewing a GenAI architecture with an engineering lead, running a discovery session with brand managers, delivering the AI transformation narrative to field sales leadership and presenting a capability roadmap to the Senior Leadership Teams. You will bring a platform-centric, reuse-first mindset: every solution you ship should be architected for scalability and accelerated deployment across indications - so a trigger framework proven in one tumor area becomes the template for the next launch.
Key responsibilities
1. Program Strategy & AI Roadmap Ownership
Own the strategy and transformation roadmap for Sales, Marketing, and Medical Affairs AI capabilities across your assigned OBU tumor-area portfolio, being responsible for planning and budget management processes in alignment with OBU annual cycle.
Develop quantifiable cases and value narratives for future Sales, Marketing, and field AI capabilities in collaboration with OBU Franchises, I&A, and Enterprise AI delivery teams; present to OBU Leadership Team (OLT) to drive top-down alignment and shared decisions on roadmap prioritization.
Maintain a prioritized product backlog with well-defined user stories, acceptance criteria, and delivery timelines; balance the portfolio across housekeeping (maintenance/refresh), innovation (new AI capability pilots), and new-indication onboarding in an agile operating model.
Track industry, market, and innovation shifts — GenAI, agentic AI, oncology data science, competitor AI strategies — to anticipate opportunities and risks and keep the roadmap forward-looking.
Champion a platform-centric, reuse-first architecture philosophy: design AI capabilities that pilot in one indication and scale across OBUs without re-platforming.
2. GenAI & Agentic AI Product Development
Lead the definition, design, and delivery of GenAI-powered applications for OBU commercial and medical teams: AI-assisted field briefing tools ( InsightIQ ), clinical evidence summarization for MSLs, agentic omnichannel workflows (Engagement IQ), and natural-language interfaces to AZBrain analytics.
Define product requirements and functional specifications for LLM-powered, RAG-based, and agentic AI applications; partner with Enterprise AI engineering leads to translate requirements into governed, scalable, production-grade solutions.
Maintain solid understanding of the evolving GenAI / agentic AI landscape — prompt engineering, RAG architectures, multi-agent orchestration, evals — and critically evaluate architecture choices against OBU field workflow requirements.
Apply rigorous pilot-and-scale methodology : define pilot scope and success criteria upfront, measure output quality and user adoption, and drive evidence-based scaling decisions to other indications and OBU functions.
3. DS&AI Business Partnership — Brand, Medical & Access
DS&AI business partner and product owner for assigned tumor-area brand teams, Medical Affairs, and Market Access — attending strategy reviews, launches, and leadership committee meetings as the AI expert at the table.
Lead cross-functional discovery workshops that reveal unmet decision needs. Develop well-scoped AI use cases using detailed problem descriptions, success metrics, data requirements, and risk tiers. Convert the results into actionable user stories for engineering teams.
Partner with MSL and medical leadership on scientific use cases: treatment-pathway analytics, KOL/KEE influence mapping (Cami constellation), diagnostics/biomarker testing strategies and health equity analytics.
Own and govern demand-sensing and care-gap workstreams feeding FSIP, forecasting, and field strategy plans; present roadmap and field impact at leadership team meetings, national sales meetings, and SteerCo forums.
4. Capability Building & Change Management
Set the direction for how OBU develops AI functions in Sales, Marketing, and Medical Affairs. Prioritize solutions that meet key business needs. Ensure these solutions are scalable, balanced, and embedded in daily field workflows.
Identify the people and process changes required to successfully stand up each AI capability; act as change leader, delivering the organizational AI transformation narrative to sales and marketing teams.
Partner with Business Excellence and Franchise teams to design and execute training plans, field enablement workshops, and persona-aligned onboarding for every major capability release.
Drive AI literacy across brand, medical, and field teams through capability reviews, lunch-and-learns, and executive presentations; build self-service fluency with AZ AI platforms.
5. Execution Excellence & Delivery Accountability
Ensure accurate and timely translation of business needs into technical requirements. Partner with the AI division passionate about enterprise solutions in data science and engineering. Establish clear RACI and maintain alignment on priorities, dependencies, and timelines across the full delivery model.
Drive launch-critical AI results on time: pre-launch analytics, ML-enriched targeting lists, EHR/claims/lab-signal predictive triggers per AIDLC framework.
Supervise progress and surface interdependencies across the product portfolio; creatively address key challenges and blockers and escalate to senior leadership with clear problem framing and proposed solutions.
Manage external vendors and consulting partners against defined deliverables and timelines; support budget management and PMO invoicing.
6. AI Innovation, Data Science & Emerging Capabilities
Identify and pilot emerging AI/ML techniques for the OBU portfolio: LLM-powered field tools, agentic frameworks, biomarker-signal models, multimodal data fusion (structured claims + unstructured clinical notes + lab signals), and RWE analytics.
Lead or co-lead data-source evaluations; articulate granularity caveats and p