Product Manager, Health AI

Additional Location(s): US-MN-Arden Hills; US-MN-Maple Grove

Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance

At Boston Scientific, we'll give you the opportunity to harness all that's within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we'll help you in advancing your skills and career. Here, you'll be supported in progressing - whatever your ambitions.

About the role:

At Boston Scientific, you'll have the opportunity to harness all that's within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information, and training, we'll help you advance your skills and career-supported in progressing, whatever your ambitions.

The healthcare industry is experiencing rapid digital transformation, reshaping patient experiences, clinical workflows, and expectations. Boston Scientific is advancing science for life by delivering secure, scalable, and responsible AI solutions that improve outcomes and enable new models of care.

As the Product Manager, Health AI, you will drive strategy execution and delivery for a portfolio of Health AI initiatives. You will translate clinical and business needs into well-governed programs, align stakeholders across divisions, and manage external partners and vendors to deliver measurable value. In this role, you will work closely 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.

Work model, sponsorship, relocation:

At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiring employees to be in our local office at least three days per week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position at this time.

Your responsibilities will include:

● 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…