Mercury - Lifecycle Marketer
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Requirements
• 4+ years of experience in lifecycle or email marketing • Hands-on proficiency with email as a channel, and in enterprise-level marketing automation tools (bonus points for experience with Customer.io) • Experience using tools like Omni, Hex, Looker, or similar to analyze marketing experiments • AI fluency with demonstrated examples of optimizing workflows and campaigns with custom skills and/or agentic flows • B2B or B2C SaaS experience is a strong plus • The total rewards package at Mercury includes base salary, equity (stock options), and benefits. • Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers. • Our target new hire base salary ranges for this role are the following: • US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $128,600 - $144,600 • US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $115,700 - $130,100 • Canadian employees (any location): CA$121,500 - $136,700
Responsibilities
• Execute and optimize customer lifecycle programs that drive product adoption, cross-sell, and upsell • Partner with growth, product, and data teams to identify friction points in the user journey and build messaging strategies that address them • Own and iterate on customer lifecycle journeys — writing briefs, managing QA, setting logic, and analyzing performance to improve conversion • Use data to inform messaging strategy and audience segmentation, working closely with data science to define and track KPIs tied to product adoption and retention • Collaborate with copywriters, designers, and product marketers to build high-quality, user-focused communications that guide users toward value • Bring a test-and-learn mindset to the role — propose experiments, launch A/B tests, and iterate based on results
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