Senior product leader, data and artificial intelligence

A leading healthcare organization is seeking a senior product leader to own and advance a high‑visibility data and artificial intelligence product. This role is responsible for setting product direction, driving execution, and ensuring measurable business impact while operating within a modern product operating model. The position requires close partnership with executive stakeholders, data science teams, and business leaders to translate complex problems into clear, value‑driven product outcomes.

This is a strategic and hands‑on role for a product professional who can balance long‑term vision with day‑to‑day delivery in a regulated healthcare environment.

Responsibilities

• Own end‑to‑end product strategy and execution for a data and AI‑driven product, ensuring alignment with business goals and value realization
• Lead and manage a cross‑functional product team, fostering accountability, autonomy, and consistent delivery
• Translate complex healthcare, economic, and data‑driven challenges into clear product roadmaps, priorities, and deliverables
• Partner closely with senior leaders to shape product vision, communicate progress, and influence strategic decisions
• Develop clear, executive‑ready narratives and presentations that articulate product direction, progress, risks, and outcomes
• Operate within and help advance a product operating model, including agile ways of working and continuous improvement practices
• Lead core product management activities such as sprint planning, backlog prioritization, and work intake using product management tools
• Coordinate across engineering, data science, analytics, and business teams to ensure alignment and timely delivery
• Act as a bridge between technical and non‑technical stakeholders, translating data science and machine learning concepts into business insights
• Ensure product initiatives are grounded in healthcare economics and tied to measurable business outcomes

Required experience and skills

• Five to ten or more years of experience across product management, strategy, or consulting roles
• Proven experience leading products across multiple stages of the product lifecycle
• Background in structured problem‑solving or strategy‑focused environments
• Strong understanding of data products and machine learning concepts, with the ability to ask the right questions and guide teams effectively
• Experience working in or alongside healthcare organizations or healthcare economics
• Demonstrated ability to structure ambiguous problems and turn them into actionable plans
• Advanced presentation and storytelling skills, including building executive‑level materials
• Proven ability to connect product initiatives to measurable business value
• Experience partnering with data science or analytics‑driven teams
• Strong communication and stakeholder management skills, with comfort operating in high‑visibility environments
• Ability to balance strategic thinking with hands‑on execution and operational product work
• Technically curious mindset with the ability to translate complex concepts into clear business outcomes

FAQ

1. What are the core responsibilities of a Senior Product Leader in data and AI?
This role defines and drives the product vision, strategy, and roadmap for data and AI-driven products. It includes identifying high-impact use cases, aligning with business objectives, and ensuring successful delivery. The leader also oversees product lifecycle management from ideation to scale.

2. What types of products does this role typically manage?
Products may include machine learning platforms, data analytics solutions, AI-powered applications, and decision intelligence systems. These products often support automation, personalization, and predictive insights. The focus is on delivering measurable business value through data and AI.

3. How does this role collaborate with technical teams?
The role works closely with data scientists, data engineers, and software engineers to define requirements and guide development. Collaboration ensures that models and systems are scalable, reliable, and aligned with product goals. Clear communication bridges technical and business perspectives.

4. What level of technical expertise is required?
A strong understanding of data platforms, machine learning concepts, and cloud technologies is essential. While hands-on coding may not be required, the ability to engage in technical discussions is critical. Knowledge of data pipelines, model deployment, and analytics is highly valuable.

5. How is success measured in this role?
Success is measured by product adoption, business impact, and the effectiveness of AI-driven outcomes. Metrics may include revenue growth, operational efficiency, and model performance. Delivering scalable and impactful solutions is key.

6. What challenges are common in this role?
Challenges include managing complex data ecosystems, ensuring data quality, and aligning stakeholders across business and technical teams. Ethical considerations and regulatory compliance in AI can also be significant. Strong leadership and decision-making skills are required.