• Design, build, and maintain robust data pipelines that ingest player, game, and marketing data from databases, event streams, and external APIs. • Develop, evaluate, and deploy machine learning models for use cases such as LTV prediction, churn forecasting, player segmentation, and marketing optimization. • Build and optimize analytical datasets and feature pipelines that support modeling, experimentation, and reporting. • Partner with Product, Game Design, Marketing, and Analytics teams to frame business questions, define success metrics, and deliver actionable insights. • Ensure data quality, reliability, and reproducibility through testing, monitoring, documentation, and version control. • Integrate model outputs into dashboards, reporting tools, or downstream systems to support operational decision-making. • Continuously improve analytical workflows, modeling approaches, and data tooling to increase accuracy, scalability, and efficiency.