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Wildlife Studios, one of the world's largest gaming companies, is seeking a Data Scientist to join its Insights team. In this role, you will transform petabytes of player data into actionable insights that directly improve game design and player experience. Working embedded with product teams, you'll tackle complex challenges including matchmaking optimization, game economy scaling, content customization, and experimental design.
Key responsibilities include applying advanced statistics and the scientific method to test hypotheses and iterate on games; analyzing large, complex player datasets to impact product strategy, retention, and monetization; partnering with Product Managers and Engineers to solve open-ended business questions; delivering solutions to core product challenges like game economy and matchmaking optimization; incorporating AI and modern tools into daily workflows; and building high-quality data products and frameworks to support team decision-making.
You should have solid applied statistics and machine learning experience with practical expertise in experimentation design, A/B testing, and predictive modeling. A product analytics mindset is essential—you'll need proven ability to analyze player behavior, formulate hypotheses, and translate data into actionable insights. Strong technical proficiency in SQL and Python (or R) is required to independently query, clean, and analyze large datasets. Comfort with AI tools like LLMs and coding assistants is important for accelerating execution and automating routine tasks.
You are business-driven and pragmatic, motivated by generating real value rather than overengineering solutions. You're a creative problem solver who loves tackling open-ended challenges and uncovering non-obvious solutions through data. You take initiative, lead execution autonomously, and keep stakeholders aligned. You're an AI enthusiast eager to test new tools and push technical boundaries. Clear communication skills—both written and spoken English—are essential for conveying complex analytical ideas to cross-functional partners.
