Product Manager - Data Science; MDM​/ Net Revenue

Product Manager - Data Science (MDM / Net Revenue)

We are looking for a Product Manager with strong Master Data Management (MDM), HCO mastering, Life Sciences domain, and Net Revenue data experience. This role will own roadmap, backlog, requirements, sprint execution, release planning, and stakeholder alignment for data products and MDM capabilities that support commercial, managed care, government pricing, chargebacks, and downstream analytics use cases.

The ideal candidate should understand MDM concepts and ETL/data pipeline processes well enough to partner effectively with data engineering, MDM configuration, QA, domain, and client-facing teams. The candidate should be comfortable translating business needs into data requirements, user stories, acceptance criteria, semantic model needs, and release-ready product capabilities.

Key responsibilities include:

• Own and manage the product roadmap, release backlog, prioritization, sprint scope, and delivery execution for assigned MDM and Net Revenue data products.
• Elicit, document, and manage business requirements, functional requirements, user stories, acceptance criteria, and data-focused use cases.
• Lead or support scrum ceremonies, sprint planning, backlog grooming, sprint reviews, retrospectives, and cross-functional delivery coordination.
• Maintain JIRA epics, stories, tasks, defects, priorities, dependencies, acceptance criteria, and release documentation.
• Define requirements for HCO mastering, golden record creation, identity resolution, survivorship, hierarchies, relationships, stewardship workflows, and data quality rules.
• Partner with Data Engineering and MDM teams on source ingestion, ETL/ELT, source-to-target mappings, transformations, validation, reconciliation, and downstream publishing needs.
• Translate requirements across Chargebacks, Government Pricing (GP), P , U , contracts, claims, sales, customer, and reference data domains.
• Support productization of key data assets such as 844, 867, 852, HIN, DEA, NPI, NCPDP, 340B, and related Life Sciences commercial data sets.
• Define test scenarios, coordinate UAT, validate requirements against delivered functionality, and ensure traceability from requirements through release.
• Facilitate workshops and working sessions with business stakeholders, domain SMEs, engineering, MDM, support, customer engagement, and leadership teams.
• Drive release readiness, release notes, rollout communication, adoption support, and post-release feedback intake.
• Create and maintain product documentation, process flows, data definitions, user guides, training material, and operational handoff documentation.

Domain expertise required includes:

• Strong understanding of Life Sciences / Pharma commercial and market access data domains.
• Experience with HCO Master Data Management, customer mastering, reference data, identity management, and data governance.
• Experience or strong working knowledge of Net Revenue systems and processes, including Chargebacks, Government Pricing (GP), P , and U .
• Understanding of industry data sets and identifiers such as 844, 867, 852, HIN, DEA, NPI, NCPDP, and 340B.
• Ability to connect domain concepts to data models, data pipelines, MDM outcomes, reporting needs, and semantic model development.

Required qualifications include:

• 8+ years of product management, product owner, business analyst, or data product experience in Life Sciences, healthcare, or enterprise data platforms.
• Hands-on experience managing product backlogs, roadmaps, JIRA boards, user stories, sprint execution, and release planning.
• Strong knowledge of Master Data Management concepts, especially HCO mastering, golden records, match/merge, survivorship, hierarchies, relationships, and data quality.
• Experience working with data engineering, ETL/ELT, data warehousing, MDM configuration, QA, and analytics teams.
• Ability to define source-to-target mapping needs, validation rules, reconciliation requirements, and data quality acceptance criteria.
• Strong understanding of Life Sciences commercial operations, market access, managed care, government pricing, chargebacks, claims, contracts, or related revenue management processes.
• Experience with Agile/Scrum delivery methodology and tools such as JIRA and Confluence.
• Strong communication skills with the ability to translate complex business and data concepts across business and technical audiences.
• Strong analytical, documentation, problem-solving, and stakeholder-management skills

Preferred qualifications include:

• Experience with Reltio, Informatica MDM, Veeva Network, One Key, or similar MDM/reference data platforms.
• Experience with Snowflake, dbt, data warehouses, semantic models, reporting layers, or AI/analytics data products.
• Experience working with commercial data feeds, claims data, chargeback data, contract data, customer master data, and reference data providers.
• Exposure to 340B covered entity data, HIN, DEA, NPI, NCPDP, PHS/OPAIS, and other authoritative data sources.
• Experience supporting AI-ready data assets, governed…