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.

Heartflow is transforming how coronary artery disease is diagnosed and managed. The Heartflow platform, including the Heartflow FFRCT Analysis and Plaque Analysis, is used by hospitals, imaging centers, and physician practices across the country, and keeping those customers successful at scale is central to our growth. We are looking for a Customer Success Analyst to join the Strategic Analytics team and serve as the analytical engine behind our Customer Success and Support organizations.

In this role, you will own the data, models, and insights that help Customer Success leaders decide how to staff, where to focus, and what to fix. You will build headcount and capacity models, turn support ticket data into clear themes and root causes, track customer health and adoption across our site base, and deliver dashboards and analyses that leadership relies on. You will work closely with Customer Success, Support, Sales Operations, Finance, and Product, translating operational questions into rigorous analysis and practical recommendations.

We are an AI-forward analytics team. The ideal candidate is someone who already uses AI tools as a core part of how they work, from accelerating SQL and Python development to classifying and summarizing unstructured ticket data, and who is excited to help build the automated, AI-assisted workflows that will define how Customer Success operates at Heartflow.

Job Responsibilities:

Capacity & Headcount Planning: Build and maintain capacity models for Customer Success and Support teams, linking case volume, site growth, ticket demand, and handle time to staffing needs; support annual planning and in-year headcount decisions.
Support Ticket Insights: Analyze Salesforce case data to identify volume drivers, recurring issues, root causes, and trends by site, product, and issue type; translate findings into actionable recommendations for Support, Product, and Operations.
Support Operations Metrics: Define and track core operational KPIs such as ticket volume, first response time, time to resolution, backlog, SLA attainment, escalation rates, and workload distribution.
Customer Health & Retention: Develop and refine customer health scoring, adoption and utilization tracking, and early-warning indicators of churn or declining engagement; partner with CS leaders to prioritize proactive outreach.
Onboarding & Time-to-Value: Measure onboarding performance and ramp of newly launched sites, identifying where customers stall and what drives faster adoption.
Dashboards & Executive Reporting: Build and maintain Tableau dashboards and recurring reports for CS and executive audiences, with clear narratives on what changed, why, and what to do about it.
Salesforce Data & Process: Partner with Sales Operations and Salesforce administrators to improve case and account data structures, ticket categorization taxonomy, and data quality so the data supports reliable analysis.