Product Owner, Applied Intelligence

Avalon Administrative Services LLC•Tampa, FL

10h•Remote

About The Position

The Product Owner, Applied Intelligence is responsible for translating business needs into scalable, data-driven and AI-enabled product capabilities. This role sits at the intersection of product, data science, and engineering - owning the delivery of intelligent features, models, and automation that enhance decision-making, operational efficiency, and customer value. This individual will actively engage business stakeholders across the organization to surface opportunities, shape priorities, and build shared understanding of AI/ML capabilities — while partnering with data scientists and engineers to bring use cases from concept to production in a reliable, compliant, and impactful way. This position is eligible for remote work, but quarterly travel will be required to Avalon’s corporate office located in Tampa, Florida.

Requirements

Bachelor’s degree
4–8 years of experience in product management, product ownership, or business analysis with exposure to data, analytics, or AI/ML-driven products.
Experience working in agile environments with cross-functional teams.
Healthcare or health-tech experience required.
Strong ability to translate complex business problems into structured product requirements.
Working knowledge of AI/ML concepts and machine learning workflows.
Excellent communication and stakeholder management skills.
Analytical mindset with a focus on outcomes and measurable impact.

Nice To Haves

Experience at a private equity-backed growth stage company

Responsibilities

Own and manage the product backlog for Applied Intelligence initiatives, including AI/ML models, analytics products, and automation solutions.
Lead ongoing backlog refinement sessions with cross-functional stakeholders to ensure priorities reflect current business needs, not just engineering capacity.
Translate business problems into clear user stories, acceptance criteria, and prioritized work for engineering and data science teams.
Partner with Engineering and Data teams in agile delivery, ensuring timely and high-quality releases.
Continuously refine and reprioritize backlog based on business impact, performance insights, and stakeholder feedback.
Proactively engage business stakeholders to identify and validate high-value opportunities for AI/ML and advanced analytics.
Support the development of use cases such as predictive modeling, decision support, anomaly detection, and workflow automation.
Act as the primary liaison between business teams and technical teams.
Drive structured discovery and prioritization processes with stakeholders.
Communicate progress, risks, and outcomes to stakeholders at all levels.
Partner with data engineering teams to ensure availability, quality, and accessibility of data.
Define and track KPIs for AI-driven features and drive continuous improvement.