Own lifecycle marketing performance across patient onboarding, activation, and retention. Design experiments, leverage SQL and AI/ML capabilities, and drive measurable improvements in intake, activation, and engagement rates.
145k – 185k
Hybrid5+ YOEGrowth Marketing
About the role
Responsibilities
Design and execute structured A/B and multivariate tests across email, SMS, and in-app channels, building experimentation roadmaps tied to lifecycle KPIs
Analyze funnel performance to identify gaps, diagnose segment and state-level variation, and translate findings into prioritized, data-backed improvements
Actively test and evaluate AI-powered capabilities within the lifecycle stack including send-time optimization, predictive segmentation, dynamic content, and propensity modeling
Partner with Data, Engineering, and Operations to integrate machine learning signals (no-show risk, churn risk, engagement propensity) into lifecycle triggers and journeys
Own the analytical layer for lifecycle performance, building, maintaining, and evolving reporting frameworks and dashboards
Write SQL queries and partner with Analytics and BI teams to surface actionable insights from patient behavior, funnel performance, and experiment results
Define success metrics, ensure proper instrumentation, and hold experiments to an incrementality bar
Diagnose state-level and segment-level performance variation
Lead through influence across Product, Operations, Marketing Operations, Data Engineering, and Creative
Partner with Technical Lifecycle and Marketing Operations to design, instrument, and launch experiments
Collaborate with Creative on messaging hypotheses, bringing behavioral data and patient insights to inform content strategy
Align with Product and Product Marketing to integrate behavioral and product signals into lifecycle programs
Requirements
5 to 8 or more years of experience in growth, lifecycle, or performance marketing with a track record of driving measurable outcomes
Strong SQL proficiency and comfort operating in data warehouses; Snowflake experience preferred
Experience designing, measuring, and iterating on structured experiments with clear understanding of incrementality
Deep familiarity with cohort analysis, funnel diagnostics, and segment-level performance variation
Genuine curiosity about AI and ML applications in lifecycle marketing including predictive modeling, dynamic content, propensity scoring, and intelligent automation
Ability to test and form opinions on new tools quickly and separate real lift from noise
Strong problem-solving skills and ability to translate complex data into clear, concise business recommendations
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