Product Analytics Manager

Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease using AI-driven, non-invasive cardiac testing. We are seeking a Product Analytics Manager to own product analytics for the Heartflow platform, serving as the analytical partner to Product, Engineering, and Commercial leaders. The role is hands-on and high-impact, covering experimentation, instrumentation, metrics, dashboards, and executive communication.

Responsibilities

Own the analytical agenda for the Heartflow platform and identify features, workflows, and behaviors that drive adoption, retention, and utilization; Design, run, and analyze experiments (A/B tests, feature flags, staged rollouts) and apply quasi-experimental methods where randomization is not feasible; Define and maintain a product metrics framework including north-star, activation, engagement, retention, and feature adoption metrics; Partner with Engineering to design and implement event tracking in Mixpanel and observability signals in Datadog, and own the tracking plan and event taxonomy; Build cohort, funnel, and lifecycle analyses and develop product health indicators; Build and maintain dashboards and self-service reporting (e.g., Tableau, Mixpanel); Define success criteria before launches, measure post-launch performance, and run structured readouts; Combine quantitative usage data with qualitative inputs such as customer feedback, support tickets, surveys, and user research; Champion AI and LLM tools across the analytics workflow; Ensure product analytics practices follow data handling, privacy, and quality policies; Present findings and recommendations to senior leadership and mentor analysts

Requirements

Deep expertise in product analytics, including experimentation design and analysis, cohort and retention analysis, funnel analysis, and feature adoption measurement; Strong statistical foundation in hypothesis testing, power and sample-size analysis, regression, and causal inference; Advanced SQL and proficiency in Python for analysis, modeling, and automation; Experience with cloud data warehouses (e.g., Amazon Redshift, Snowflake, BigQuery); Strong BI and data visualization skills with tools such as Tableau or similar; Hands-on experience with product analytics and observability platforms such as Mixpanel, Amplitude, or Datadog, including designing event schemas and tracking plans with Engineering; High AI fluency with daily, practical use of LLM tools (e.g., Claude, ChatGPT, Copilot); Ability to translate ambiguous business questions into structured analyses and turn complex results into actionable recommendations; Proven cross-functional collaboration with Product, Engineering, Design, Customer Success, and Commercial teams; Strong product sense and business acumen; Highly organized and self-directed, with a commitment to data quality and analytical rigor; Bachelor's degree in a quantitative field such as Statistics, Economics, Computer Science, Mathematics, Engineering, or a related discipline; 8+ years of experience in analytics, data science, or a related field, including at least 3 years focused on product analytics; Demonstrated track record of designing and analyzing experiments that influenced product decisions; Experience leading analytics instrumentation projects in partnership with Engineering

Nice to have

Experience in B2B SaaS, healthcare technology, or medical devices; Familiarity with healthcare data privacy requirements (e.g., HIPAA) and working in a regulated environment; Experience mentoring or managing analysts; Master's degree; Experience with semantic layers or metrics stores (e.g., Cube, dbt); Curiosity about how AI can automate analytics workflows and power new products

Benefits

Cash bonus