Lifecycle Marketing Manager

Notion•San Francisco, CA

2d•$150,000 - $210,000•Hybrid

About The Position

Notion is seeking an experienced Lifecycle Marketer to join their Product team. This high-impact role will be responsible for rethinking and managing the growth engine that drives customer engagement and retention. The position involves building intelligent, always-on growth programs to help users discover features, build confidence, and deepen product usage. The Lifecycle Marketer will partner with Product Growth, Engineering, Product Marketing, and Data Science to create personalized experiences across channels like email and in-product, using AI and automation to enhance efficiency and effectiveness. A key aspect of the role is to act as a customer advocate, synthesizing user feedback and behavioral data to inform product decisions and go-to-market strategies. The position requires a strong understanding of MarTech systems, data pipelines, and experimentation, with a focus on leveraging AI to scale impact and improve program velocity and quality.

Requirements

8–10 years experience in lifecycle marketing, product management, growth marketing, product marketing, or product-led engagement, with PLG experience preferred
Proven track record owning always-on, triggered lifecycle programs end to end that drive measurable adoption, retention, and monetization outcomes
Strong MarTech system fluency in concepts such as reverse ETL, data pipelines, APIs, webhooks, and more that enable you to build workflows from brief to build, to launch and measure
Systems mindset and love for building repeatable processes and improving tooling to scale quality and velocity with the help of AI and Agents. You can answer the question of “what have you built with AI in the last 90 days?”
Comfort with designing A/B tests with pre-registered hypotheses and holdout groups. You can explain statistical significance to a non-technical stakeholder.
Strong customer empathy and segmentation instincts—able to synthesize qualitative + quantitative inputs into clear audience definitions, intent models, and lifecycle interventions.
Excellent messaging and copy craft with a user-first lens, able to turn fuzzy problems into clear narratives and next best actions
Strong storytelling and stakeholder management skills, with the ability to turn insights into clear strategy, priorities, and persuasive narratives
Analytical strength and ability to define success metrics, partner with Data and Engineering on eventing, and evaluate results with discipline
You don’t need to be an AI expert, but you’re curious and willing to adopt AI tools to work smarter and deliver better results.

Nice To Haves

Experience across B2B, B2C, and B2C2B surfaces and journeys
Experience with Customer.io, Figma, HTML, and basic SQL
Comfort using AI and automation tools to streamline lifecycle operations and enable personalization at scale
Experience partnering closely with Product Growth teams and shipping in high-velocity environments

Responsibilities

Own always-on lifecycle journeys end-to-end: Design and run growth programs that drive adoption, repeat usage, and monetization outcomes, turning "first try" into "part of how I work”. Act as a strategic operator, you’ll bring work from high-level strategy through to launch, owning everything in between.
Build systems that scale: Bring systems thinking to how Lifecycle Marketing operates—from intake and campaign execution to QA, measurement, and channel governance—using AI and automation to increase velocity and quality across programs.
Demonstrate deep technical fluency: Leverage knowledge of reverse ETL, data pipelines, APIs, webhooks, and event-based triggers to design sophisticated, personalized journeys that go beyond the traditional MarTech stack.
Translate customer signals into targeted engagement: Synthesize research, support, community, and sales inputs into audience definitions and behavioral triggers that deliver the right message at the right moment—across email and in-product—for every user context, from new members to power users.
Run rigorous experimentation: Partner with Data and Product to define hypotheses, implement tracking, measure lift, and share learnings. Bring alignment on lifecycle touchpoints with Product Growth and PMMs to ensure cohesive, not disconnected, experiences.
Tell the story of what's working: Turn engagement data, experiment results, and behavioral patterns into clear readouts, roadmap influence, and persuasive narratives for stakeholders.