Location: Remote, only open to candidates based in Latin America**
About the Role
tapouts is looking for a Data & Analytics Lead to build the analytical foundation guiding our growth, product, and coaching operations, answering questions like what it costs to acquire a customer, why customers churn, and how we measure coaching quality.
This is a hands-on role combining business and product analytics with analytics engineering. This is not primarily an infrastructure role, we're looking for someone as comfortable investigating an ambiguous business question as they are writing SQL and building a data model.
What You'll Do
- Establish clear, shared definitions for core metrics: acquisition, activation, retention, churn, CAC, and lifetime value
- Build a unified view of the customer journey across marketing, payments, product activity, coaching sessions, and cancellations
- Develop retention and churn analyses that identify when and why customers leave
- Create a framework for evaluating coach quality, incorporating outcomes, engagement, and satisfaction
- Build and maintain clean, documented analytical data models and decision-oriented dashboards
- Identify gaps in tracking and data quality, partnering with engineering and business teams to resolve them
- Partner with growth, product, operations, and coaching leadership to turn business questions into measurable analyses
What Success Looks Like
Within your first three months, you will:
- Understand and document tapouts major data sources and customer journey
- Align the organization on definitions for its most important business metrics
- Deliver a reliable initial view of acquisition, retention, churn, and coaching activity
- Produce at least one analysis that changes or informs an important business decision
Within six to twelve months, you will:
- Establish a trusted analytical data foundation used across the company
- Give leadership reliable visibility into CAC, retention, lifetime value, and unit economics
- Build a fair and actionable framework for measuring and improving coaching quality
What We're Looking For
- Strong experience in product analytics, business analytics, analytics engineering, or a similarly hands-on data role
- Advanced SQL skills and experience working with imperfect data from multiple systems
- Strong business judgment — the ability to translate ambiguous questions into measurable analyses
- Experience with customer funnels, cohort analysis, retention, churn, segmentation, CAC, and lifetime value
- Experience building analytical data models in a modern data warehouse
- Comfort operating independently in an early-stage environment with limited existing data infrastructure
Nice to Have
- Experience with subscription, marketplace, education, coaching, or consumer services businesses
- Familiarity with Python, dbt (or comparable transformation tools), and modern BI platforms
- Experience as an early or first data hire
Who Thrives in This Role
You're naturally curious about customers and the business behind the data. When someone asks for a dashboard, you first ask what decision they're trying to make. You move easily between detailed technical work and conversations with company leaders, and you enjoy creating structure where little currently exists.
