Data Analyst - Leaply

Навыки

• A/B-тесты
• Amplitude
• API (интеграции)
• Атрибуция
• BI-инструменты
• BigQuery
• CAC / CPA / CPL

О компании и продукте

• We're looking for a 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.
• Scale the function. You'll help evolve how Leaply does marketing analytics — the tools, the pipelines, the standards behind every decision.

Задачи

• 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
• What You’ll Need to Succeed
• 2+ years in analytics for consumer apps or digital products, ideally subscription-based
• Strong analytical mindset — you decompose metric behavior naturally, separate cohort from calendar effects, and explain complex concepts in plain language
• Strong SQL with hands-on experience on large datasets (BigQuery would be a plus)
• Proficiency with BI tools (Tableau preferred
• Power BI, Looker). A track record of building automated reporting layers would be a plus
• Solid grasp of core marketing economics — CPM, LTV, CAC, ROAS — and how they connect to business decisions (performance marketing background would be a plus)
• Comfort with experimentation methodology and statistical fundamentals — A/B test design, sample sizing, significance, power, common pitfalls
• It’s great if you have
• Working-level Python for data manipulation and lightweight scripting
• Hands-on Amplitude experience — both dashboard building and tracking design
• Experience with a data transformation tool (dbt, Dataform, SQLMesh)
• Data Science fundamentals — forecasting, clustering, basic ML approaches
• Experience running monetization experiments (significant plus in a subscription context)
• A natural teacher instinct — you proactively level up the team around you, not just deliver numbers

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