Marketing Analyst

Hi! We’re Leaply — a product ecosystem in the Health & Wellness niche. Our mission is to create a platform users can fully trust with their health, so they can live healthier on autopilot. We launched in 2024 and have already seen explosive growth — 10x revenue in the past six months — with strong traction across the US, Europe, and beyond.

At Leaply, we challenge traditional career paths — we value ownership over job titles, and impact over process. As we scale, we're looking for a sharp, data-driven Marketing Analyst to bring structure and clarity to how we make marketing decisions.

Role Overview:

We're looking for a Marketing Data Analyst to own and elevate marketing analytics across Performance Marketing. The Marketing team at Leaply is highly data-driven and focused on developing at-scale, measurable marketing programs designed to improve the lifetime value of Leaply customers.

This is a high-impact individual contributor role for someone who thrives in complex environments and brings structure, clarity, and insight where systems are still evolving.

You'll be the primary analytical partner for the Performance Marketing team, with broad ownership over measurement frameworks, reporting, A/B test evaluation, LTV prediction, analytical culture development, and strategic decision support. Your job is to improve processes that already work and unlock the zones we haven't gotten to yet.

What You Will Do:

• Partner with the marketing team to sharpen day-to-day decision-making — from spend allocation to creative testing to channel mix

• Drive analytical culture across the marketing team — through training, self-service tooling, and enablement that turns data into a team capability, not an analyst service

• Prioritize and lead deep-dive research into our audience and how each segment translates into long-term unit economics

• Build out our AB test evaluation framework across funnels — set methodology, raise the quality bar, accelerate decision velocity

• Design and own the monitoring layer for key metrics and early warning signals — dashboards, AI assistants, Slack alerts.

• Design and evolve scalable, resilient data pipelines that consolidate marketing, product, and payment data into analytics-ready models

• Partner with engineering on the quality and transparency of our tracking — from event taxonomy to attribution integrity

• Shape team-level standards: which tools we use, how we approach recurring analytical problems, what "good" looks like for us