Heartflow - Product Analytics Manager

• 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. • Product insights & strategy: • 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. • Experimentation: • 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. • Metrics framework: • 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. • Instrumentation & tracking: • 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. • Retention & cohort analysis: • 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. • Dashboards & self-service BI: • Launch measurement: Define success criteria before launches, measure post-launch performance, and run structured readouts so the organization learns from every release. • Launch measurement: • 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. • Voice of customer: • 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. • AI-enabled analytics: • 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. • Data governance & compliance: • Communication & leadership: Present findings and recommendations to senior leadership with clear narratives and visuals; mentor analysts and raise the bar for analytical rigor across the team. • Communication & leadership: • Deep expertise in product analytics, including experimentation design and analysis, cohort and retention analysis, funnel analysis, and feature adoption measurement. • Strong statistical foundation: hypothesis testing, power and sample-size analysis, regression, and causal inference techniques for situations where clean randomization is not possible. • 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; experience with semantic layers or metrics stores (e.g., Cube, dbt) is a plus. • 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: daily, practical use of LLM tools (e.g., Claude, ChatGPT, Copilot) to accelerate analysis and coding, plus curiosity about how AI can automate analytics workflows and power new products. • Ability to translate ambiguous business questions into structured analyses and to turn complex results into clear, actionable recommendations for technical and non-technical audiences. • Proven cross-functional collaboration with Product, Engineering, Design, Customer Success, and Commercial teams; comfortable influencing without direct authority. • Strong product sense and business acumen, with the ability to connect user behavior to customer value and company outcomes. • Familiarity with healthcare data privacy requirements (e.g., HIPAA) and working in a regulated environment is a plus. • Highly organized and self-directed, with a bias for action and a commitment to data quality and analytical rigor. • Educational Requirements & Work Experience: • Bachelor’s degree in a quantitative field such as Statistics, Economics, Computer Science, Mathematics, Engineering, or a related discipline; Master’s degree preferred. • 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. • Experience in B2B SaaS, healthcare technology, or medical devices strongly preferred. • Experience mentoring or managing analysts preferred. • The salary range for this position is $155,000 - $200,000 and cash bonus. #LI-Hybrid