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Product Manager, Health AI

Job in Marlborough, Middlesex County, Massachusetts, 01752, USA
Listing for: Boston Scientific Gruppe
Full Time position
Listed on 2026-05-16
Job specializations:
  • IT/Tech
    Data Security, Cybersecurity, AI Engineer (Applied/Software), Data Analyst
Salary/Wage Range or Industry Benchmark: 106800 - 202900 USD Yearly USD 106800.00 202900.00 YEAR
Job Description & How to Apply Below

About the role

At Boston Scientific, you will drive strategy execution and delivery for a portfolio of Health AI initiatives, translating clinical and business needs into well-governed programs. The role requires collaboration with AI Engineering, Platform teams, Enterprise Architecture, Data and AI Governance stakeholders, and Business Units to ensure solutions are feasible, integrated with enterprise standards, validated for clinical and technical performance, and ready for scaled adoption.

Hybrid work model: employees are required to be in our local office at least three days per week. This position is not subject to visa sponsorship.

Your responsibilities
  • Deliver cross-divisional Health AI initiatives with clinical, R&D, and operational stakeholders by translating needs into well-defined programs, platform‑enabled capabilities, and release plans with clear milestones, dependencies, and success criteria.
  • Facilitate end‑to‑end roadmaps and execution by establishing phase gates from discovery through pilot, validation, launch, and scale, ensuring readiness across clinical, technical, financial, and operational dimensions.
  • Establish and manage enterprise Health AI preferred partnerships and vendor ecosystems that divisions can leverage to accelerate solution development and deployment, driving cost sharing, standardized onboarding, enterprise agreements, and reusable integrations.
  • Partner with divisional product teams to define and mature strategic programs, including imaging algorithm development, data interoperability, and hospital solution implementation, ensuring each initiative has clear roadmaps, financial plans, governance, and resourced execution teams.
  • Support divisions in defining integration and implementation strategies for third‑party data sources, such as EMR and EHR systems, aligning to enterprise standards for data governance, privacy, cybersecurity, and interoperability, including HL7 and FHIR where applicable.
  • Enable divisions to build AI and machine learning‑enabled diagnostics and longitudinal care solutions by coordinating cross‑functional requirements, risk assessments, and controls to support safe AI‑enabled workflows across care settings.
  • Partner with divisions to accelerate physician workflow efficiency and improve clinical decision support by supporting adoption planning, training approaches, and change management with clinical and hospital stakeholders.
  • Coordinate with AI Engineering, clinical experts, and divisional teams to set imaging AI initiatives up for success, including validation plans, dataset strategy, performance metrics, bias and risk considerations, and post‑deployment monitoring expectations.
  • Support hospital‑ready scalability by aligning deployment models, cybersecurity requirements, support models, and operational SLAs, while promoting reusable, enterprise‑grade capabilities that reduce duplication and accelerate time to value.
  • Lead partnership selection and validation for Health AI vendors, including strategic fit, technical and Responsible AI due diligence, and clinical value assessment.
  • Coordinate vendor onboarding to meet enterprise needs across divisions, establishing long‑term collaboration models, integration standards, and governance expectations.
  • Manage vendor deliverables, contractual milestones, and performance in partnership with divisions, Procurement, Legal, Privacy, and Security teams.
  • Champion agile and compliant Health AI delivery practices in collaboration with divisions and data and AI delivery teams, leveraging AI‑enabled tools for backlog management, sprint planning, and progress reporting.
  • Collaborate with Responsible AI, Regulatory, and Quality teams to standardize documentation, decision gates, and risk management artifacts, including alignment with software lifecycle controls and SaMD expectations where applicable.
  • Collaborate with divisions and delivery teams to define and report KPIs for adoption, outcomes, operational impact, and financial value realization, supporting corrective actions when needed.
  • Provide regular updates to leadership and governance councils, clearly communicating progress, risks, decisions required, and recommended…
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