Lifecycle Marketing Manager
crypto:applicationbusinessM2Growth Marketing
Compensation
Not disclosed
About the role
We're hiring a Lifecycle Marketing Manager to join our Product and Lifecycle Marketing team. In this role, you'll design and optimize lifecycle programs that engage, retain, and grow members across their entire journey with Chime—from top of funnel through long-term retention—with a clear focus on driving growth, revenue, and member lifetime value (LTV).
This is a role for a holistic, business-minded marketer rather than a single-channel specialist. You'll think in terms of segments, experiments, and outcomes: building targeted campaigns across the channels we own—push, in-app, and out-of-app (email, SMS)—while connecting those touchpoints with the broader, non-owned channels that shape the member experience. You'll partner closely with cross-functional teams to turn data into segmentation, automation, and personalization strategies that move the business.
This is a role with department-level impact: you'll own diverse projects, exercise significant independent judgment, and influence how members experience Chime across the full lifecycle.
If you're creative, dedicated, and love working in a fast-paced environment alongside passionate colleagues, we want to meet you.
The base salary offered for this role and level of experience will begin at $139,000 and up to $181,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
In this role, you can expect to
Own full-funnel lifecycle strategy—from top of funnel through activation and long-term retention—building targeted campaigns that drive growth, revenue, and member LTV.
Define segments and translate them into targeted, personalized campaigns across owned channels (push, in-app, and out-of-app), connecting them with the broader non-owned channels that shape the end-to-end member experience.
Generate data-driven hypotheses and run experiments