Sr. Director, Dynamic Measurement and Testing AI Product Owner, AIA

ROLE SUMMARY

As we actively advance Marketing AI agenda Commercial AI Council is seeking a Dynamic Measurement and Testing AI Product Owner own the end-to-end delivery of the following prioritized AI use cases:

• Pfizer Insights Engine: Single agentic platform that gathers and consolidates relevant internal and external insights for a brand, its indication(s), and the market, and provides tactical recommendations to brand owners

• Omni-channel Orchestrator: Decision engine to identify the right time to engage HCPs, and decide optimal journey, touchpoints and messaging across channels to maximize impact and conversion

• Dynamic Measurement and Testing: Real-time testing and measurement platform that enables querying, summary and extraction of KPIs and budget information to make budgeting decisions less laborious and make spend more effective

• Unified Marketing Interface: Unified UI/UX for marketers to access all AI capabilities across their day-to-day needs

You will lead a cross-functional squad (data science, ML engineering, full-stack, solution architecture, design/UX, agent ops, and business translators) to turn high-value marketing use cases into reliable, compliant, and measurable AI capabilities for marketing teams in the US market. You’ll lead the work from discovery to scaled adoption to align roadmap, governance, and outcomes, in coordination with the commercial AI council, Digital and other key stakeholders to ensure marketing AI efforts are in sync with the organizational vision.

ROLE RESPONSIBILITIES:

• Translate approved business cases into an actionable pod roadmap; define scope, milestones, success metrics, and risks

• Own the backlog: intake, refine, size with the team, and prioritize to maximize value within capacity constraints

• Ensure design readiness: partner with translator/UX to keep problem statements, flows, prompts, and UI specs current

• Align with governance: confirm data access, model/feature approvals, risk controls, and compliance requirements before build

• Lead the pod through iterative development of models, prompts/agents, services, UI, and integrations; uphold coding, model, and prompt standards

• Release readiness: create implementation and test plans, run go/no-go with stakeholders, and schedule deployment windows

• Execute releases with DevOps/engineering; verify PRs/approvals are complete and standards met

• Run smoke tests in UAT and Production; validate guardrails, logs, and monitoring are live

• Coordinate enablement: short how-tos, quick-start guides, and in-flow training; collect structured user feedback in the first weeks post-launch

• Operate the capability against SLOs/SLAs (latency, accuracy, availability, cost)

• Triage and resolve user issues; communicate updates and workarounds

• Be the day-to-day point of contact for business owners; set expectations, surface trade-offs, and communicate progress and risks

• Track and report KPIs: business outcomes, adoption/active users, quality, incident trends, and delivery predictability

• Ensure all work adheres to AI and data governance (privacy, responsible AI, brand, medical/legal/regulatory as applicable)

Team & ways of working

• Lead a 6-10 person pod

• Create a culture of clarity, speed, and accountability

• Collaborate with platform/enterprise tech teams on architecture, data pipelines, MLOps, compliance and security

• Escalate capacity and dependency risks early; make crisp trade-off calls aligned to the marketing AI roadmap

BASIC QUALIFICATIONS:

• Bachelors Degree required

• 12+ years of experience leading cross-functional commercial projects (graduate degrees can be substitute for experience)

• Understanding of AI and machine learning frameworks and libraries

• Experience in leading teams

Preferred Qualifications:

• Experience with cloud platforms and tools for deploying AI models, such as AWS, Google Cloud, or Azure.

• Experience in AI development, including hands-on experience with designing, training, and deploying AI models.

• Ability to lead and inspire a team, fostering collaboration and innovation.

• Strong project management skills, including the ability to plan, execute, and deliver projects on time.

• Excellent communication skills for articulating complex technical concepts to non-technical stakeholders.

• Strategic thinking to align AI initiatives with bu