Senior Lifecycle Marketing Manager

Responsibilities

• Own measurable performance improvements across the patient lifecycle, including onboarding, activation, early care, and long-term retention.
• Design and execute structured A/B and multivariate experiments across email, SMS, and in-app channels.
• Build experimentation roadmaps tied to lifecycle KPIs such as no-show/late-cancel rates, visit completion, and retention.
• Analyze funnel performance, cohort behavior, segment and state-level variation, and experiment results to identify prioritized improvements.
• Evaluate AI-powered lifecycle capabilities, including send-time optimization, predictive segmentation, dynamic content, propensity modeling, and intelligent automation.
• Partner with Data, Engineering, and Operations to integrate machine-learning signals such as no-show risk, churn risk, and engagement propensity into lifecycle triggers and journeys.
• Validate model performance, monitor for drift, and ensure AI-assisted decisions are grounded in patient outcomes and business impact.
• Own lifecycle reporting frameworks and dashboards, providing a real-time view of lifecycle health.
• Write SQL queries and partner with Analytics and BI teams to surface actionable insights.
• Define success metrics, ensure proper instrumentation, and require evidence of incrementality before acting on experiment results.
• Lead cross-functional alignment across Product, Operations, Marketing Operations, Data Engineering, Creative, and Product Marketing.
• Collaborate with Creative on messaging hypotheses and use behavioral data and patient insights to inform content strategy.

Requirements

• 5–8 or more years of experience in growth, lifecycle, or performance marketing with a track record of measurable outcomes.
• Strong SQL proficiency and experience working in data warehouses.
• Experience designing, measuring, and iterating on structured experiments.
• Understanding of incrementality and its importance in experimentation.
• Deep familiarity with cohort analysis, funnel diagnostics, and segment-level performance variation.
• Curiosity about AI and machine-learning applications in lifecycle marketing, combined with the analytical rigor to evaluate them critically.
• Ability to learn and assess new tools quickly and distinguish genuine lift from noise.
• Strong problem-solving skills and ability to translate complex data into concise business recommendations.

Nice-to-haves

• Snowflake experience.
• Experience with predictive modeling, dynamic content, propensity scoring, or intelligent automation in lifecycle marketing.

Compensation and Benefits

• Annual salary: $145,000–$185,000.
• Medical, dental, and vision benefits effective on day one.
• 401(k) with company match.
• Generous paid time off and paid holidays.
• Paid parental leave.
• Learning and career development opportunities.