[Hiring] Data & Analytics Lead @tapouts

Role Description

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

Qualifications

• 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.