Manager, Data Specialist

The AI Acceleration (AIA) function within the Chief Marketing Office (CMO) is the single, business‑led engine that owns the design, delivery, and scale‑up of priority AI capabilities across commercial operations. AIA works in tight collaboration with various Pfizer functions to deploy and maintain production‑grade AI solutions that simplify how we work and drive measurable value across all processes.

• Engage directly with commercial business stakeholders—including Brand, Sales Operations, Market Access, Content Generation, and Medical—to elicit, clarify, and document data and analytics requirements.
• Decompose high‑level business needs into structured data engineering work items including data product definitions, pipeline specifications, transformation logic, and acceptance criteria.
• Facilitate working sessions between business users and engineering teams to align on scope, timelines, and technical feasibility.
• Serve as the primary point of contact for data‑related inquiries from commercial analytics and AI/ML teams, triaging requests and ensuring efficient backlog management.

• Author detailed data product specifications including source‑to‑target mappings, business rules, data dictionaries, and field‑level definitions.
• Define and document data quality expectations, validation rules, and SLA requirements in collaboration with data engineering and governance teams.
• Maintain and continuously improve data documentation artifacts within the enterprise data catalog to support self‑service discovery and AI‑readiness.
• Partner with data architects to ensure proposed data products align with the enterprise semantic layer and are optimized for downstream AI/ML and analytics consumption.

• Translate prioritized business requirements into well‑defined user stories, epics, and technical tasks within the data engineering development backlog.
• Collaborate with data engineers to refine tickets, clarify ambiguities, and provide domain context that enables efficient, high‑quality delivery.
• Track progress of data engineering deliverables, identify blockers, and communicate status and impacts to business stakeholders in a clear, non‑technical manner.
• Validate delivered data products against requirements and coordinate user acceptance testing with business teams prior to production release.

• Champion data quality by defining, monitoring, and communicating metrics that measure the reliability, completeness, and timeliness of commercial data assets.
• Work with data governance and compliance teams to ensure data products adhere to applicable privacy, regulatory, and data stewardship standards relevant to commercial pharma (e.g., IQVIA, CRM, HCP/HCO data).
• Identify and document data lineage, ownership, and usage policies for commercial data domains.

• Understand and support the data requirements of AI/ML and advanced analytics use cases, including feature engineering inputs, model training datasets, and inferencing pipelines.
• Coordinate with data scientists and ML engineers to ensure data products are structured, enriched, and accessible in formats optimized for model development and deployment.
• Contribute to the continuous improvement of data standards that ensure commercial AI initiatives are built on a trusted, governed data foundation.

• Bachelor’s degree with at least 4 years of experience; OR master’s degree with at least 2 years; OR PhD with 0+ years; OR associate’s degree with 8 years; OR high school diploma (or equivalent) with 10 years of relevant experience.
• Experience in a data‑focused role such as business analyst, data analyst, data product manager, or comparable function within a data‑intensive organization.
• Demonstrated experience translating business requirements into technical specifications for data engineering or BI/analytics development teams.
• Experience in the pharmaceutical, biotech, or life sciences industry, particularly within a commercial analytics or sales operations function.
• Familiarity with commercial…