● 実験・運用基盤活用スキル:A/Bテスト基盤やRemote Config等を理解し、配信後も安全にバランス調整・検証を回せる能力
● モデリング/シミュレーション設計スキル:経済・継続・収益をモデル化(予測)し、設計の意思決定に使える能力
● 経済循環(Source/Sink・報酬ペース)設計スキル:通貨/報酬の供給と消費を設計し、インフレ/枯渇を抑えられる能力
● 定量バランシングスキル:期待値・難易度曲線・勝率データを用いて、調整を再現性高く行えるの能力
● A/Bテストフレームワークおよびライブバランシングツールの理解
● 経済シミュレーション、リテンションモデリング、マネタイズ設計のバックグラウンド
● ソース/シンク設計、報酬ペーシング設計の実務経験
● 期待値モデリング、難易度曲線設計、勝率ベースバランシングの経験
● Game Desginerのコミュニケーションの共通基盤(UA / Retention / Engagement / Monetization / LiveOps)を、プレイヤー体験を軸として根拠と事例で語れる方
● 仮説→実装(仕様化)→計測→学習を高速で回し、最適解を更新し続けられる方
● 関係者との合意形成の段階で、選択肢としての「新しい視点」を常に提示する姿勢が取れる方
● データドリブンでありながら、プレイヤー体験の本質を見失わない方
● 仮説検証を高速で回し、数字で語れるデザイナー
● 経済設計とゲーム体験のバランスを俯瞰できるシステム思考の持ち主
● Data Science/Product/LiveOpsと対等に議論できる論理性を持つ方
● 変化を楽しみ、新しい最適解を探し続けられる方
As a Game Designer focused on Monetization and Offer Design, you will own the strategy and execution of in-game offers — including pricing, contents, and presentation — to drive CVR, ARPDAU, and LTV.
You will operate at the intersection of economy design, player psychology, and live data optimization, ensuring that monetization initiatives enhance both revenue performance and long-term player experience.
This is a high-ownership role requiring executive-level communication, structured experimentation, and strong economic thinking.
● Design monetized offers (pricing, content bundles, presentation timing) to increase CVR, ARPDAU, and LTV
● Define segment-based value design and Expected Value (EV), and continuously optimize in live environments
● Analyze purchase funnels and monetization correlations, translating insights into actionable improvements
● Maintain healthy Source/Sink balance and protect long-term economic stability
● Collaborate cross-functionally to establish A/B testing plans and monetization design rules
● Design and balance mechanics and progression systems that reinforce player flow, engagement, and retention
● Continuously tune systems post-launch using live player data
● Analyze win rates, retention deltas, gameplay curves, and economy metrics to optimize balance
● Define difficulty curves, reward pacing, and EV models across player segments
● Partner with Data Analysts to evaluate completion rates, retry rates, booster usage, and spend correlations
● Lead live tuning cycles (hypothesis → implementation → measurement → iteration)
● Collaborate with UX, Art, and Engineering to optimize clarity, feedback loops, and conversion touchpoints
● Document tuning frameworks, monetization logic, and economic systems for cross-team alignment
● F2P System & Monetization Design Expertise Ability to integrate difficulty, progression flow, and economy (rewards/pricing/monetization) in Puzzle/Merge genres and clearly explain their impact on Retention and LTV
● Data-Driven Optimization Ability to derive strategies from win rates, EV, ARPDAU, retention deltas, CVR, and live KPIs, executing rapid hypothesis → implementation → measurement → learning cycles
● Specification & Alignment Communication Skilled in structuring PRDs, mock-ups, and measurement requirements; clearly communicating expected impact, risks, and design rationale across Engineering, Art, QA, Analytics, and LiveOps
● Production Planning & Efficiency Ability to estimate level production scope and propose productivity improvements, including AI-assisted workflows
● Deep understanding of how difficulty, economy systems, and offer design impact retention and monetization
● Strong quantitative analysis skills, translating metrics into actionable design decisions
● Experience with capacity planning in casual genres (including automation and AI tools
● Comfortable iterating quickly based on live KPIs and player feedback
● Ability to thrive in Agile environments
● Experience in hybrid-casual genres
● Strong understanding of experimentation infrastructure (A/B testing frameworks, Remote Config systems)
● Modeling and simulation skills for economy, retention, and revenue forecasting
● Expertise in economic circulation design (Source/Sink balance, reward pacing, inflation control)
● Quantitative balancing skills using Expected Value modeling, difficulty curves, and win-rate data
● Background in economy simulation, retention modeling, and monetization design
● Hands-on experience with live balancing tools