Product Analytics Manager

Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease, the #1 cause of death worldwide, using cutting-edge technology. The flagship product—an AI-driven, non-invasive cardiac test supported by the ACC/AHA Chest Pain Guidelines called the Heartflow FFRCT Analysis—provides a color-coded, 3D model of a patient’s coronary arteries indicating the impact blockages have on blood flow to the heart. Heartflow is the first AI-driven non-invasive integrated heart care solution across the CCTA pathway that helps clinicians identify stenoses in the coronary arteries (RoadMap™Analysis), assess coronary blood flow (FFRCT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). Our pipeline of products is growing and so is our team; join us in helping to revolutionize precision heartcare.

Heartflow is a publicly traded company (HTFL) that has received international recognition for exceptional strides in healthcare innovation, is supported by medical societies around the world, cleared for use in the US, UK, Europe, Japan and Canada, and has been used for more than 750,000 patients worldwide.

As Heartflow's product portfolio expands, understanding how customers adopt, use, and get value from our products has become central to how we build and grow.

We are seeking a Product Analytics Manager to own product analytics for the Heartflow platform. Reporting to the Director of Strategic Analytics, you will be the analytical partner to Product, Engineering, and Commercial leaders, answering questions such as which features drive retention and utilization, what separates high-adoption sites from low-adoption ones, and whether a new capability actually changed behavior. You will design and run experiments, build the instrumentation and data foundations that make product behavior measurable, and turn insights into clear recommendations that shape the roadmap.

This is a hands-on, high-impact role for someone who is equally comfortable defining an event taxonomy with engineers, writing complex SQL, building an executive dashboard, and presenting a point of view to senior leadership. You will also help lead the way in applying AI to analytics, using modern AI tools to accelerate analysis, automate recurring work, and make product insights accessible across the company.

Job Responsibilities:

• Product insights & strategy: Own the analytical agenda for the Heartflow platform; identify the features, workflows, and behaviors that drive adoption, retention, and utilization, and translate findings into prioritized recommendations for Product and Commercial leadership.
• Experimentation: Design, run, and analyze experiments (A/B tests, feature flags, staged rollouts) with rigorous hypotheses, power analysis, and success metrics; where randomized tests are not feasible, apply quasi-experimental methods (e.g., difference-in-differences, matched cohorts, interrupted time series) to estimate impact.
• Metrics framework: Define and maintain a product metrics framework, including north-star, activation, engagement, retention, and feature adoption metrics, with clear, governed definitions that tie product usage to commercial outcomes such as site utilization and revenue.
• Instrumentation & tracking: Partner with Engineering to design and implement event tracking in Mixpanel and observability signals in Datadog; own the tracking plan and event taxonomy, and establish QA processes that keep product data accurate, complete, and trustworthy.
• Retention & cohort analysis: Build cohort, funnel, and lifecycle analyses at the user and site level to understand ramp, engagement, and churn risk; develop product health indicators that help Customer Success and Sales act early.
• Dashboards & self-service BI: Build and maintain dashboards and self-service reporting (e.g., Tableau, Mixpanel, semantic-layer tools) that give Product, Engineering, and executive stakeholders real-time visibility into product performance.
• Launch measurement: Define success criteria before launches, measure post-launch performance, and run structured readouts so the organization learns from every release.
• Voice of customer: Combine quantitative usage data with qualitative inputs (customer feedback, support tickets, surveys, user research) to build a complete picture of the customer experience.
• AI-enabled analytics: Champion the use of AI and LLM tools across the analytics workflow, from code generation and automated analysis to natural-language access to product data, and help build AI-assisted tools that scale the team’s impact.
• Data governance & compliance: Ensure product analytics practices follow Heartflow’s data handling, privacy, and quality policies, partnering with Data Engineering, Security, and Quality/Regulatory teams as needed in our regulated medical device environment.

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