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Data Analyst

TrulyRemote Verified

Hand-curated global remote job with direct application link

Technical Requirements

SQLTableauGoogle Tag ManagerGA4AmplitudePythonR

What you will do:

  • Analyze player behavior across the full funnel: registration, first deposit, retention, reactivation, churn - and translate findings into actionable product recommendations.
  • Design, run, and interpret A/B tests and quasi-experiments, handling the methodology for measuring feature impact.
  • Build and maintain cohort-based analyses (LTV, retention curves, payback) to support product and investment decisions.
  • Define, validate, and monitor product KPIs and metric trees, challenging metrics that do not reflect real business value.
  • Partner with product managers to prioritize the roadmap based on expected impact.
  • Develop self-service dashboards (Tableau) and data sources to help stakeholders answer routine questions.
  • Investigate anomalies in key metrics and communicate root causes clearly to non-technical audiences.
  • Maintain a culture of rigorous, honest analytics: document assumptions, quantify uncertainty, and flag limitations in data.
  • Own web analytics implementation and data quality, including tracking plans, event taxonomy, tag management (GTM), and validation of new releases.

What we need from you:

  • 2+ years of experience in Product, Web, or Data analytics.
  • Hands-on experience with web analytics platforms (GA4, Amplitude, Mixpanel, or similar), specifically in event design and tracking implementation.
  • Working knowledge of Google Tag Manager or comparable systems, including the ability to read dataLayer specs and debug tracking issues.
  • Strong SQL skills, including window functions, CTEs, and experience with large datasets (e.g., Athena).
  • Solid grounding in statistics, including hypothesis testing, confidence intervals, statistical power, and identifying common pitfalls like selection or cohort-maturity bias.
  • Proven experience with funnel analysis, cohort analysis, LTV, and retention modeling.
  • Proficiency with a BI tool, preferably Tableau, including data source design.
  • Understanding of attribution models and their limitations.
  • Proficiency in Python or R for ad-hoc analysis is a plus (pandas, curve fitting, survival analysis).
  • Intermediate proficiency in English (written and spoken).
  • Experience with iGaming, fintech, or high-frequency B2C domains is a plus.
Data Analyst
Growe
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