We're looking for a talented and passionate Senior Data Scientist to join Wildlife's Marketing Tech team in São Paulo, Brazil.

Wildlife is one of the largest mobile gaming companies in the world. A big part of that success is acquiring users more efficiently, and we do this through a mathematical understanding of market and user dynamics. We believe that our models are a core part of our edge, and we're looking for people to push them further.

As a Senior Data Scientist, you'll play a key role in sharpening that edge: how to handle data from millions of users more efficiently and effectively, how to better understand the mechanics of dozens of different channels, how to make sure we're operating thousands of campaigns the right way, among many others.

You'll be surrounded by exceptionally talented people: data scientists, engineers, and marketers who are among the best in the industry at what they do, in an environment where the bar is high, and learning happens fast.

The right person for this position is naturally curious, thrives when left to take initiative on their own, loves solving problems and puzzles, is resilient, and enjoys being in a fast and growing business.

Main Challenges

The team is responsible for designing, building, and evolving data-intensive applications. As a Senior Data Scientist, you will be part of a cross-functional team, directly contributing to:

• Directly shape how we deploy millions of dollars in Marketing by modeling player behavior at scale.
• Continuously improve our performance measurement framework, which includes estimating the causal impact of each campaign and the lifetime value of our users to understand the long-term return on our Marketing investments;
• Create and improve the tools to optimize our acquisition campaigns;
• Build the capabilities to run experiments to continuously improve the performance of our creative assets and our Marketing operations;
• Support the decision-making of our Marketing operations through high-quality data products and well-structured dashboards;
• Disrupt the status quo by incorporating agentic AI in the day-to-day operations: building agents that monitor, diagnose, and act on our campaigns, and a framework for continuous improvement of our end-to-end ecosystem.

What you'll need

• Experience applying appropriate statistical or machine learning techniques in different situations (e.g., causal inference, experimentation design, predictive models, etc)