Director, Oncology Commercial Data Science & AI Products

Werebuilding a connected end-to-endEnterprise AIengine - uniting data foundations AI technology process reinvention and business-facing AI to accelerate results across the whole value depends on being exceptional connectors:youllactivelyleverageexisting 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 - youll have the platform (and sponsorship) to make it real.

Our DS&AI Products team is the OBUs 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 notan analyticsconsulting 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 salesleadershipand 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 portfoliobeing responsible forplanning and budget management processes in alignment withOBUannual 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 toanticipateopportunities and risks and keep the roadmap forward-looking.

• Champion a platform-centric reuse-first architecture philosophy: design AI capabilities that pilot in oneindicationand 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 toAZBrainanalytics.

• Define product requirements and functional specifications for LLM-powered RAG-based and agentic AI applications;partnerwith Enterprise AI engineering leads totranslaterequirements 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-scalemethodology: 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 testingstrategiesand 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 andSteerCoforums.

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.

• Identifythe people and process changesto 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

• Ensureaccurateandtimelytranslation of business needs into technical requirements. Partner with the AI division passionate about enterprise solutions in data science and engineering. Establish clear RACI andmaintainalignment 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

• Identifyand 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 preprocessing requirements to both technical and business audiences.

• Design and implement the OBU predictive ML trigger ecosystem for earlier patient identification across indications with reusable frameworks that scale across tumor areas.

• Drive precision-medicine and earlier-patient-identification strategies: design AI trigger frameworks that detect high-risk patients upstream of clinical decision points reducing diagnostic and treatment lag.

7. AI Governance Compliance & Data Stewardship

• Operate within AstraZenecas enterprise AI governance framework: registry-before-scale model and data cards human-in-the-loop oversight ongoing monitoring and IT approval processes.

• Navigate compliance requirements data access controls HIPAA privacy guardrails and vendor management for all OBU AI use cases; ensure all products are deployed responsibly withappropriate documentation.

• Partner with OBEX FSIP Legal Privacy and I&A to ensure AI-ready data assets (enriched claims EHR MMIT) are compliant auditable and operationalized with standardized QA and refresh cadences.

• Maintain auditable AIDLC; govern UAT compliance approval release gates with scenario-based stakeholder demonstrations and documented acceptance criteria.

8. Impact Measurement & Value Tracking

• Define success criteria and KPIs before launch; supervise adoption metrics (apputilization trigger execution rate noise reduction coverage) output quality and downstream business impact (sales lift patient-identification speed care-gap closure) post-launch.

• Lead causal-impact assessments to quantify commercial lift attributable to triggers and AI applications; use findings to guide cross-OBU collaboration and investment decisions.

• Communicate results to OBU and enterprise leadership with clarity translating product performance data into business impact narratives that reinforce AI investment decisions andadvisefuture roadmap prioritization.

Essential Requirements

• Bachelors degree or comparable experience in a quantitative field like CS statistics engineering economics or similar. Advanced qualifications including an MBA MS PhD or equivalent experience are highly valued.

• 710 years of professional experience with 5 years in pharma commercial functions (or pharma-focused strategy consulting);demonstratedend-to-end AI/data-science product ownership with measurable commercial impact in an oncology or specialty context.

• Strong analytical fluency able to translate between brand strategy commercial operations data science and technology teams; experienced at bridging business and technical stakeholders across a highly matrixed organization.

• Hands-on familiarity with LLMs crafting input queries retrieval-augmented generation systems and agentic frameworks (LangChainLlamaIndex or equivalent); workingproficiencyin Python and ML/AI tooling; experience with cloud platforms (AWS SageMaker/Athena Databricks Azure or GCP).

• Deepexpertisein oncology commercial data: secondary claims (IQVIA Symphony MMIT) EHR/EMR sources such as Komodo and Veeva PULSE lab/diagnostic data (Diaceutics) specialty pharmacy and enriched ML assets.

• Exceptional communication skills and proventrack recordtooperatesuccessfully in highly matrixed organizations; effective interpersonal and relationship-management skills with a consultative approach.

• Strong initiative: ability to understand core business goals set direction build alignment and drive work forward proactively; resourceful and influential in a fast-growing organization.

Preferred Qualifications

• Graduate degree (MBA MS MD or PhD) in a quantitative scientific or business discipline.

• Demonstrated commercial experience in Oncology

• Production GenAI / agentic AI experience in commercial pharma: LLM-powered field tools RAG-based clinical applications or agentic omnichannel workflow automation under enterprise governance.

• Experience with KOL/KEE influence analytics precision-targeting tools (e.g. EGFR-testing waypoint analysis) or omnichannel NBA platforms (Aktana Veeva Align).

• Track recordof leading AI-enabled business transformation and change management programs across large organizations (1000 users).

• External thought leadership: conference presentations or publications in oncology analytics or commercial AI

Technical competency profile

Ideal candidates willdemonstrateapplied depth across:

GenAI & Agentic AI

• LLMs and prompt engineering: GPT-4 / Claude / Gemini family; system prompting few-shot chain-of-thought structured output

• RAG architectures: vector stores chunking strategies retrieval evaluation hallucination mitigation

• LLMOps: evaluation pipelines output quality monitoring A/B testing for GenAI applications

Classical ML & Data Science

• Supervised/unsupervised learning: logistic regression gradient boosting (XGBoost/LightGBM) clustering propensity scoring for patient/HCP targeting

• Time-series and sequence models for patient-journey stage prediction and trigger timing optimization

• Causal inference and test-and-control methodologies for AI impact attribution and commercial ROI measurement

Data & Cloud Platforms

• Oncology data: IQVIA (NPA XPONENT DDD) Symphony MMITSaleSEER Komodo Veeva PULSEDiaceutics Definitive Health

• Cloud: AWS (S3 Athena SageMaker Bedrock) Databricks Snowflake; languages: Python SQL R SAS

• BI & visualization: Tableau Power BI Alteryx

Product & Delivery

• Agile/scrum: backlog grooming sprint planning user story writing acceptance criteria UAT management release approval

• AI governance: model/data cards registry workflows compliance documentation evidence frameworks

• UX collaboration: wireframing user research persona development prototype feedback cycles with field and HQ teams

• Omnichannel integration: trigger-code design message alignment field activation workflow.

Office Working Requirements

When we put unexpected teams in the same room we unleash bold thinking with the power to inspire life-changing -person working gives us the platform we need to connect work atpaceand challenge perceptions.Thatswhy we work on average a minimum ofthree days per weekfrom the office. But thatdoesntmeanwerenot flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

The annual base pay (or hourly rate of compensation) for this position ranges from $186.01440 - 279.02160 USD Annual either as annual basepayor as the hourly rate (annual base pay divided by 2080 hours). Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors including market location job-related knowledge skills and addition our positions offer a short-term incentive bonus opportunity; eligibility toparticipatein our equity-based long-term incentive program (salaried roles) to receive a retirement contribution (hourly roles) and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program 401(k) plan; paid vacation and holidays; paid leaves; and health benefits including medical prescription drug dental and vision coveragein accordance withthe terms and conditions of the applicable plans.Additionaldetails of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired employee will be in an at-will position and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time including for reasons related to individual performance Company or individual department/team performance and market factors.

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