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About the Role
This role owns the full analytics loop for a live-service game, acting as an analyst, analytics engineer, and internal-tools builder. AI coding agents handle much of the hands-on work, while the role provides the critical judgment on what to measure, the plausibility of results, and when further investigation is needed.
Responsibilities
- Own analytics across content releases, live events, monetization, the in-game economy, and player behavior, from ambiguous questions to clear recommendations.
- Write complex SQL against large, messy, semi-structured event data.
- Design and evaluate A/B tests, and reach sound conclusions when clean experiments are not possible.
- Reconcile metrics across sources and explain discrepancies.
- Use AI agents as the primary tool for analysis, engineering, and reporting, while critically evaluating their output.
- Maintain a critical eye on AI output, identifying flawed logic, bad data, or analyses that answer the wrong question.
- Build shared context and processes to ensure reliable AI-assisted analysis for oneself and others.
- Assist less technical teammates in safely answering their own questions.
- Build bespoke internal dashboards and tools focused on actual decision-making needs, prioritizing adoption as the measure of success.
- Work closely with users to understand their needs and iterate on tools post-launch.
- Own tools end-to-end, including data pipelines, interfaces, deployment, and iteration.
- Build and maintain scheduled pipelines for data feeding tools.
- Develop models and simulations for forecasting, economy and event simulation, probability, expected value, and ML-based content scoring.
- Make tools usable beyond the data team through clear documentation, APIs, and integrations.
- Translate findings into concrete recommendations for product, art, live operations, and external partners, and track them through to implementation.
- Manage recurring performance reporting and target tracking, explaining drivers of results above or below plan.
- Serve as a thought partner on design and planning decisions, not just a data provider.
Requirements
- Strong SQL and Python for analysis.
- Applied statistics knowledge, with practical understanding of methods for noisy, skewed, real-world data and their limitations.
- Comfort building and deploying small services and data pipelines.
- Fluency with AI coding agents and associated workflows.
- Familiarity with applied ML (embeddings, similarity, scoring) is a plus.
- Ability to identify when a number is nonsensical and investigate before reporting.
- Skill in setting up analyses to accurately answer questions, including comparing like with like, separating real effects from noise or shifts in measurement, and recognizing data limitations.
- Understanding of free-to-play games, including monetization (gacha), live events, virtual economies, and player segment behavior.
- Ability to explain methods in plain language and write for decision-makers, focusing on interpretation rather than restating numbers.
Skills
- SQL
- Python
- Applied Statistics
- Data Pipelines
- AI Coding Agents
- Machine Learning (ML)
- Forecasting
- Simulation
- A/B Testing
- Data Analysis
- Dashboard Development
- Internal Tool Development