Game Designer (iGaming)

💼 Experience & Knowledge

• 2–3+ years in analytics: product, monetization in a real money casino.
• Basic understanding of unit economics (CAC, LTV, ARPU, ARPPU, churn).
• Knowledge of monetization models: subscriptions, in-app purchases, bonuses, promotions, events.

• General understanding of demand elasticity, incentive mechanics, and reward systems.

   

💻 Technical Skills

• SQL – solid knowledge (joins, aggregations, CTE, basic window functions).
• Excel/Google Sheets – financial and scenario modeling.
• Basic Python/R for data processing or statistics (a plus, but not required).
• Experience with at least one BI tool (Tableau, Power BI, Looker, Metabase).

🤝 Soft Skills

• Attention to detail, structured thinking.
• Ability to explain results to colleagues without technical backgrounds.
• Teamwork with product, marketing, and analytics departments.
• Responsibility for the accuracy of calculations and models.

⭐ Nice to Have

• Experience in gaming, gambling, fintech, or subscription products.
• Experience with simulations or forecasting models (even basic level).
• Interest in game design or behavioral economics.

Key Responsibilities

• Product Economy Analysis

Monitor core product economics metrics (CAC, LTV, ARPU, ARPPU, churn, payback) to evaluate monetization efficiency across user segments. Conduct cohort analysis, assess retention impact after product updates or events, and identify revenue imbalances.

• Monetization, Bonuses & Events

Analyze the effect of bonuses, promotions, and in-product events on revenue and user behavior. Calculate bonus ROI, assess welcome offers, and test new reward mechanics to ensure they boost engagement and retention without harming profitability. Build “what-if” models to simulate changes in rewards, event frequency, or progression systems.

• Forecasting & Modeling

Develop revenue, ARPU, and LTV forecast models and simulate potential outcomes of product economy changes. Evaluate medium-term (3–6 month) impact of pricing or bonus adjustments. At senior level — apply causal inference, regression, or MMM models to measure the true effect of marketing and monetization initiatives.

• A/B Testing & Experiments

Support the design and analysis of experiments, such as pricing tests, new bundles, promotions, or reward systems. Measure statistical significance, evaluate impact on conversion, ARPU, and retention, and provide recommendations on scaling.

• Product & Marketing Decision Support

Act as a data partner for Product and Marketing teams, evaluating the financial viability of new features or campaigns. Provide insights, recommendations, and analytical inputs for roadmap planning and quarterly OKRs. At senior level — advise CPO/CMO on monetization strategy, demand elasticity, and revenue structure.

• Monitoring & Reporting

Build and maintain dashboards (Tableau/Power BI/Metabase), track anomalies in revenue and user behavior, and deliver regular performance reports to product teams. Ensure transparency of the product economy and early detection of risks (bonus inflation, payer conversion drop, etc.).

🎁 What We Offer

• 💰 Competitive salary
• ⚡ Exciting technical challenges and complex tasks to help you grow
• 💼 A strong senior+ level team you'll want to work and learn with
• 🚀 Minimal bureaucracy — maximum action. Flexible processes, fast decisions
• 🏠 Remote-first approach: work wherever you're comfortable (or visit the office)
• 🎓 Investment in learning: internal knowledge sessions, external courses, certifications
• 🍻 Work-life balance: no overtime, no micromanagement
• 🖥 Modern equipment: MacBook, Starlink, PowerBank — everything you need for productivity
• 👶 Bonuses for maternity leave and child birth
• 🔔 And many more internal perks that are better to show than describe