Senior Growth & Marketing Analyst

Alloy Health is the leading direct-to-consumer women’s digital health company providing expert care and personalized solutions for women in midlife. They are seeking a Senior Growth & Marketing Analyst to partner with C-level leadership to optimize and scale the marketing engine, owning the full marketing funnel and delivering actionable insights based on complex data analysis.

Responsibilities:

• Own end-to-end analysis of the marketing funnel — from acquisition through conversion, retention, LTV, and lifecycle — surfacing the drivers, friction points, and opportunities that shape growth strategy
• Proactively monitor funnel performance and deliver clear, actionable recommendations on what's moving, what's stalling, and why
• Develop scalable analytical frameworks that give the team durable visibility into funnel health, not just point-in-time answers
• Establish and maintain performance metrics that connect Marketing activity to overall Business KPIs, creating a clear line of sight between channel execution and company outcomes
• Define and implement a channel attribution framework that gives the team a rigorous, consistent methodology for evaluating how each channel contributes to conversion and revenue
• Own channel attribution modeling — designing and maintaining the frameworks that tell us how each channel is contributing to conversion and revenue
• Quickly and accurately root-cause performance anomalies, validate campaign results, and distinguish signal from noise across channels
• Partner with leadership to define measurement priorities and build a roadmap that keeps attribution methodology current as the channel mix evolves
• Manage and monitor data flows between marketing tools and the data warehouse, ensuring data is accurate, timely, and reliable for analysis
• Establish the tools, processes, and data standards needed to support a scalable marketing analytics function — building infrastructure that grows with the business, not around it
• Work directly with the CMO and C-suite as a day-to-day analytical partner — present in marketing meetings, fluent in business priorities, and trusted to bring the analytical perspective to strategic conversations
• Translate complex findings into clear, confident narratives for senior, non-technical audiences — delivering 'what this means and what we should do,' not just data
• Negotiate analytical scope with stakeholders — pushing back where needed, aligning on the right question before building the solution, and managing expectations on timelines and outputs
• Serve as the go-to resource for fast-turn, high-stakes analytical questions — structuring ambiguous problems quickly and delivering rigorous answers at the speed the business requires
• Design and execute deep-dive analyses that go beyond surface metrics to uncover the underlying dynamics driving performance
• Build solutions that scale — reusable frameworks, documented methodologies, and outputs that the team can build on rather than start over from
• Build dashboards and self-serve reporting tools that give the Growth & Marketing team direct access to the data they need, reducing analytical bottlenecks

Requirements:

• 5+ years of experience in an analytical role with significant depth in growth or marketing analytics
• D2C or e-commerce experience is non-negotiable. You must have worked inside a D2C or e-commerce business and have a genuine understanding of how the marketing engine works end-to-end — paid acquisition, conversion optimization, retention, lifecycle, CAC, and LTV. Familiarity with the category isn't enough; you need to have lived it
• Expert SQL skills and hands-on experience working directly in a cloud data warehouse (BigQuery preferred)
• Deep experience with channel attribution modeling and a clear point of view on methodology
• Proven ability to communicate complex analysis to senior, non-technical audiences including C-level stakeholders
• Strong stakeholder management skills — able to negotiate scope, align on requirements, and build scalable solutions rather than one-off analyses
• Comfort operating in a fast-moving environment where the business needs answers quickly and ambiguity is the norm
• Python preferred for regular use in analysis, not just in theory
• Experience with customer segmentation, funnel diagnostics, and lifecycle or retention modeling
• Familiarity with BI and analytics tools (e.g., Looker, Amplitude, Tableau, Mode)
• Familiarity with foundational GenAI concepts and their application in analytics workflows