AI Lead Product Manager (Healthcare, Remote or Milan)

Job summary

This senior leadership role involves owning and driving the strategy and execution of AI-powered Health Data Products, focusing on clinical, genomic, and operational data. The position requires a blend of product expertise and team leadership to deliver measurable value through AI solutions in healthcare.

Qualifications

• Bachelor's or Master's degree in Health Informatics, Data Science, Computer Science, or Business.
• Over 5 years of product management experience with a focus on data-intensive AI products in healthcare or life sciences.
• Proven experience in managing and mentoring product managers, fostering team capability and culture.
• Strong understanding of AI and machine learning concepts applied to health data.
• Exceptional stakeholder management skills across multiple geographies.
• Experience in defining and executing complex product roadmaps.
• Knowledge of healthcare data standards and privacy regulations (e.g., GDPR, HIPAA).
• Native English speaker or C1/C2 English certification.

Responsibilities

• Define and own the global product strategy and roadmap for AI-powered Health Data Products.
• Lead and develop a team of product managers, promoting a culture of collaboration and improvement.
• Engage with executive stakeholders to align on product priorities and ensure market fit.
• Champion data-driven decision-making and measure impact through OKRs and KPIs.
• Collaborate with healthcare customers to identify workflows and opportunities for AI improvements.
• Ensure each product has a solid business case and complies with regulatory requirements.
• Communicate progress and risks to stakeholders and oversee cross-portfolio dependencies.

Skills

• Strong grasp of AI and machine learning applications in health data.
• Exceptional stakeholder management and influencing skills.
• Experience with agile product development practices.

Education

• Bachelor's or Master's degree in a relevant field.

Tools

• Familiarity with health data platforms, data lakes, and AI regulatory requirements.