Jobs at Pfizer

Leads chargeback, pricing, and gross-to-net analytics for Pfizer’s U.S. hospital injectable and biosimilar portfolio. The role models contracting, rebate, government pricing, and commercial impacts on revenue, margins, and profitability; supports forecasting, accruals, reconciliations, and financial reporting; manages pricing data repositories; and advances automation, dashboards, and AI-enabled analytics. Partners extensively with Commercial, Finance, Controllership, Government Pricing, and Accounting while ensuring compliance with accounting and pricing governance requirements.

Leads learning measurement and impact strategy across Pfizer’s commercial learning portfolio. Defines evaluation standards, metrics, and success measures; oversees behavior- and business-level studies; validates relationships between learning, competency, and business outcomes; presents evidence and recommendations to senior leaders; and builds the organization’s measurement practice and analytical capabilities.

Supports Pfizer CentreOne’s inside sales and marketing activities by reviewing and routing marketing-qualified leads, executing outreach sequences, documenting activity in Salesforce, and assisting with campaigns, content, meetings, reporting, and marketing projects. The role develops commercial expertise across marketing, inside sales, and business development while progressing leads toward initial meetings and BD handoff.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Owns Pfizer GH&B’s AI-ready Snowflake data warehouse, data architecture, ontologies, governance, quality, lineage, access controls, and production reliability. The role supports AI/ML models, dashboards, and business-critical data applications; establishes testing, release, monitoring, and incident processes; directs contingent technical resources; and aligns business-specific data decisions with enterprise standards. Requires strong SQL, Python, Collibra, data warehousing, unstructured-data architecture, ontology, governance, and stakeholder-influence experience.