
// Open Role at Wildlife Studios
Join Wildlife's Insights team as a Data Scientist to transform petabytes of player data into actionable decisions, optimizing game features like matchmaking, economies, and content for a world-leading mobile game developer.
We're looking for a talented and passionate Data Scientist to join Wildlife's Insights team in São Paulo, Brazil.
Wildlife is one of the largest gaming companies in the world. As a Data Scientist on our Insights team, you will turn petabytes of player data into actionable decisions to make our games better. Working embedded with product teams, you will tackle complex quests, like optimizing matchmaking, scaling game economies, customizing content, and designing smart experiments to help us build games we are truly proud of.
We know that the work we do has a high impact on our company's success and culture. The right person for this position is naturally curious, comfortable in a "take the initiative" environment, loves solving problems, and can thrive in a fast and growing business.
Wildlife is one of the world's leading mobile game developers and publishers. We have released more than 60 titles, reaching billions of people around the globe. Here, we create games that will excite, intrigue, and engage our players for years to come!
Wildlife is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based on race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.
Solid understanding and practical experience applying statistical techniques to product problems, including experimentation design, A/B testing, and predictive modeling. Proven ability to analyze player behavior, formulate hypotheses, and translate data into actionable insights for Product Managers and Engineers. Strong proficiency in SQL and Python (or R) to query, clean, and analyze large datasets independently. Comfort and interest in using AI tools (such as LLMs or coding assistants) to speed up execution and automate routine tasks. Ability to structure complex findings clearly and communicate effectively with cross-functional partners in written English.