Marketing Analyst

RealPlay LTD is a fast-growing and innovative startup in the Gaming industry, specializing in managing online social casino games for the US market. We're looking for a talented and passionate Senior Marketing Analyst to join our Data team. Join us at RealPlay, where we believe that play isn’t just entertainment — it’s essential. We're passionate about creating engaging, data-driven digital experiences that delight and inspire players across the globe.

You’ll own the end-to-end experimentation and analytics program behind our gameplay experience—designing A/B tests, choosing the right statistical methods, and building the dashboards and pipelines that make results trustworthy and actionable. You’ll work cross-functionally with Product, Marketing, Data Engineering, and Leadership to drive retention and monetization.

Responsibilities

• Help Refine the Experimentation Pipeline: define the roadmap, write pre-analysis plans, run power/MDE estimates, set guardrails, and ensure clean randomization & exposure.
• Build from scratch: event/metric definitions, bucketing & assignment, SRM checks, data quality monitors, statistical methods and reproducible analysis pipelines (versioned, code-reviewed).
• Analyze large, complex gameplay datasets to uncover opportunities that improve gameplay, boost retention, and increase monetization.
• Develop and maintain dashboards (Looker preferred) and recurring reports that surface KPIs, experiment outcomes, and cohort/DoW/hour seasonality.
• Partner across the org to translate findings into product changes; quantify impact and close the loop post-launch.
• Mentor analysts and up-level experimentation and data literacy across teams; document standards and best practices.
  
  

• 2+ years of hands-on analytics experience (gaming/consumer product a plus) with a track record of leading A/B tests end-to-end.
• Expert SQL over large/complex schemas; comfort with window functions and performance tuning.
• Proficiency in Python or R for statistical analysis and notebooks
• Strong grasp of experimental design & statistical inference: power analysis, MDE, multiple testing control, variance reduction, non-parametrics, and modeling for low-count data (Poisson/Binomial).
• Experience building or operationalizing dashboards (ideally Looker) and turning metrics into decisions.
• Excellent communication: can turn complex analysis into crisp, actionable guidance for stakeholders.
• Curiosity and product sense; bias to measure, learn, and iterate.
  
  

• Experience with BigQuery (or similar cloud warehouses) and orchestration (Airflow/Composer).
• Causal inference methods (DID, synthetic control) and uplift modeling.
• Monte Carlo simulation for test planning and sensitivity analysis.