Data & Analytics Lead

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.
Originally posted on Himalayas