Growth Analytics Lead (Individual Contributor)

Want your work to directly influence how a 9-figure brand invests millions in growth?

Freebird® is a high-growth DTC brand redefining shaving for millions of people. We have served over 2 million customers and scaled to 9 figures in revenue.

We are entering our next phase of profitable scale and are looking for a hands-on Growth Analytics leader to build and run the intelligence engine behind it.

This is not a reporting-only role.
This is a commercial analytics role at the core of the business.

You will build the models, dashboards, and decision frameworks that determine where we scale, where we pull back, and how we increase long-term contribution margin per cohort.

Your work will directly influence marketing investment, CAC guardrails, retention-adjusted economics, and 24-month cohort contribution margin performance.

Important context

This is an individual contributor role. There is no team to start and no expectation of building one in the near term. You should be excited to get your hands dirty pulling data, building systems, and shipping dashboards yourself.

The Mission

Architect and operate the intelligence system that guides Freebird’s growth engine.

Ensure Freebird grows profitably by aligning how we acquire customers with how they perform over time.

In a subscription business, growth is driven by customers, retention, and contribution margin. Paid media impacts CAC. Creative impacts performance. Ecommerce impacts CVR and AOV. Retention impacts churn. Finance owns margin inputs.

Left unaligned, this creates drift.

You will connect these systems by building a unified measurement and decision layer that links spend, cohort behavior, retention, payback, and contribution margin into a single economic view that leadership can act on.

What You’ll Do

Scale acquisition profitably

• Guide and optimize spend so it scales efficiently under contribution margin guardrails
• Define CAC ceilings tied to 12- and 24-month contribution margin
• Model diminishing returns and marginal efficiency curves to inform budget allocation
• Translate attribution constraints and measurement uncertainty into practical, decision-ready frameworks
• Interpret insights from MMM, incrementality tests, lift studies, or MTA frameworks and translate them into practical budget and investment decisions
• Identify which channels, audiences, creatives, and offers drive the highest-quality cohorts
• Support structured validation of new channels before meaningful scale
• Deliver clear monthly recommendations on where to scale, hold, or cut

Increase 24-month contribution margin per cohort

• Build and maintain 12- and 24-month contribution margin tracking by acquisition cohort
• Develop survival curve diagnostics and retention performance visibility across key milestones
• Operationalize retention-adjusted CAC and payback thinking into acquisition decisions
• Identify acquisition sources that degrade churn, payback, LTV, or margin
• Evaluate pricing, discounts, and offers against downstream margin impact
• Create cohort-based forecasting views that improve decision quality without turning this role into FP&A

Own measurement infrastructure and dashboards (a meaningful early focus)

• Own tracking health across ad platforms, GA4, server-side events, ecommerce, and subscription systems
• Standardize UTMs, taxonomy, and core metric definitions so performance reporting is trusted
• Partner with Finance to align revenue, refunds, COGS, and contribution margin inputs
• Build automated dashboards and reduce manual reporting
• Create a clear source of truth for acquisition efficiency and long-term cohort performance

Analyze experimentation and performance changes (not designing experiments)

• Analyze tests and performance shifts across pricing, trial structure, billing cadence, onboarding, churn interventions, win-back, and upsell
• Provide decision criteria rooted in long-term contribution margin, not isolated metric lifts
• Deliver clear narratives on what changed, why it changed, and what to do next

What Success Looks Like

• Marketing efficiency improves year over year
• Spend scales confidently under clear contribution margin guardrails
• 24-month contribution margin per cohort increases materially
• Retention-adjusted CAC becomes a core decision metric
• Forecasts and dashboards are trusted across Growth and Finance
• Growth decisions become proactive rather than reactive
• Manual reporting is substantially reduced through automation and systemization

Requirements

Must-haves

• Strong track record as a hands-on, high-output analytics operato