Senior Manager, Data Science & AI (Technical Product Owner)

The International Data Science & AI organization is committed to transforming data into actionable intelligence and scalable AI capabilities that enable markets to drive better decisions, improved customer engagement, and measurable business outcomes.

We are seeking a Sr Manager – Data Science and AI, to own the critical end‑to‑end AI for Targeting & Segmentation program for international markets, including program strategy, model design, solution, product roadmap, delivery coordination across stakeholders, and value realization. This is a senior team lead role with significant influence, requiring strong cross‑functional leadership across Data Science, Analytics, BT, ICO,  Digital, and country teams to design, deploy, and scale segmentation solutions.

The successful candidate will thrive in a fast‑paced, highly collaborative environment, translate business needs into clear product/program requirements, and drive industrialization of segmentation capabilities from pilots through scalable deployments—while operating within governance, privacy, and responsible AI practices.

ROLE RESPONSIBILITIES

AI for Segmentation Program Ownership (International)

• Own the vision, strategy, and roadmap for the AI for Targeting & Segmentation program across international markets, ensuring alignment to commercial priorities and market needs.

• Define the program operating model, key deliverables, success measures, and cadence for planning, prioritization, and decision‑making across regions and markets.

• Serve as the primary point of accountability for program outcomes, coordinating across functions and markets to deliver high‑quality solutions on time and with measurable impact.

Roadmap Translation, Requirements, and Delivery Coordination

• Translate business needs into clear problem statements, requirements, and user stories for Data Science, Analytics Engineering, and Technology teams, including data needs, model requirements, workflows, and integration expectations.

• Partner closely with Data Science and engineering teams to shape solution design, ensure feasibility, and drive progress from pilot → deployment → scaling while maintaining quality, usability, and robustness.

• Establish and maintain program plans (milestones, dependencies, risks, and mitigations), and provide transparent updates to stakeholders across geographies and time zones.

Cross**‑**Functional & Market Partnership (Influence Without Authority)

• Build strong relationships with international and local stakeholders (Commercial, Marketing, Digital, Field/Operations, Tech/IT) to align on priorities, secure input, and drive adoption.

• Facilitate workshops and working sessions to align on segmentation objectives, market readiness, change impacts, and enablement needs, ensuring consistent engagement and shared ownership.

• Coordinate with centralized and regional teams to identify reusable patterns and accelerate cross‑market scaling while respecting local context, constraints, and regulatory requirements.

Adoption, Change Management, and Enablement

• Define and execute an international adoption and change management approach, including market onboarding, training, communications, and “how to use” guidance for segmentation outputs and workflows.

• Create and maintain program documentation and business‑facing assets (e.g., value proposition, playbooks, FAQs, release notes, training materials, and adoption metrics).

• Incorporate feedback loops (user feedback, performance monitoring, market learnings) to continuously improve segmentation models, outputs, and end‑to‑end user experience.

Governance, Data Privacy, and Responsible AI

• Ensure program alignment with data governance, privacy, security, and responsible AI practices, coordinating required reviews and documentation with the appropriate governance bodies.

• Partner with Technology/IT and data teams to ensure appropriate controls for data access, model monitoring, auditability, and lifecycle management.

Value Realization, KPIs, and Performance Management

• Define, monitor, and communicate program success metrics (e.g., adoption, business value, segmentation performance, operational efficiency), and drive actions to close performance gaps.

• Quantify and communicate value delivered through AI for Segmentation to senior stakeholders, connecting program outcomes to measurable market impact.

Ways of Working / Agile Delivery

• Act as “voice of the user” for international markets in agile delivery teams, helping prioritize work to maximize value and ensure usability and scalability of deliverables.

• Promote consistent ways of working across markets (templates, standards, release cadence, and minimal viable onboarding kits) to accelerate delivery and reduce rework.

BASIC QUALIFICATIONS

• Bachelor’s degree in analytics related area (Data Science, Computer Engineering, Computer Science, Statistics, Economics, Mathematics, Operations Research, Information Systems, Engineering, or a related discipline)

• 9+ years of relevant work experience delivering Analytics, Data Science, AI/ML, or Digital/Data products in a business environment, with demonstrated end-to-end ownership from problem framing to outcomes

• 4+ years of hands-on Product Management experience

• Demonstrated experience translating business priorities into clear requirements and roadmaps and leading delivery across cross-functional stakeholders (including influence without direct authority)

• Strong stakeholder management and communication skills: ability to distill complex analytical concepts into clear, decision-oriented insights for technical and non-technical audiences

• Strong program/project management skills: ability to define scope/deliverables, manage dependencies, monitor progress, and drive implementation and adoption.

• Experience working with data and analytics ecosystems (e.g., data platforms, BI, analytics engineering) and collaborating with engineering teams to operationalize solutions.

• Ability to operate effectively in a multi‑country, international environment, partnering across regions and time zones.

PREFERRED QUALIFICATIONS

• Advanced degree in Data Science, Computer Engineering, Computer Science, Information Systems or related discipline

• Experience in segmentation (customer/HCP, account, or analogous segmentation), targeting, portfolio planning, or decision support, including measurement of impact and adoption.

• Experience in product ownership and/or agile delivery practices for analytics/AI solutions, including backlog management and value-based prioritization.

• Experience in developing Machine Learning based products, preferably with Large Language Models and GenAI solutions

• Experience in developing and operating analytic workflows and model pipelines that are parametrized, automated and reusable

• Experience developing and deploying data and analytic products for use by technical and non-technical audiences

• Pharma & Life Science commercial functional knowledge

• Pharma & Life Science commercial data literacy

• Experience with Dataiku Data Science Studio

PROFESSIONAL CHARACTERISTICS

• Growth Mindset: Actively seeks improvement, evaluates the impact of insights, and helps partners anticipate strategic changes.

• Analytical Thinker: Synthesizes information across data sources into clear insights and recommendations; connects analytics to business drivers and value.

• Strong Communicator: Translates technical outputs into actionable commentary that enables effective decisions; adapts style to audience.

• Relationship Manager / Influencer: Builds durable partnerships across levels and functions; positively influences without formal authority.

• Highly Collaborative: Shares responsibility and credit; works effectively across teams; supports others through knowledge sharing and teamwork.

• Strong Program Manager: Defines scope, success criteria, and action plans; sequences work appropriately; monitors outcomes and drives adoption.

• Proactive Self**‑**Starter: Comfortable with ambiguity; prioritizes competing demands; stays current on analytics/AI trends and applies them pragmatically.

NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS

Ability to work non-traditional work hours interacting with global teams spanning across the different regions (eg: North America, Europe, Asia)

ORGANIZATIONAL RELATIONSHIPS

• Other AI and Data Science COE Teams

• Other AIDA teams (Domain Delivery, Platforms, and Support)

• Global Commercial Analytics

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

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