Data Scientist, Mobile User Acquisition

marketing mix models, and create systems that allow us to understand-and optimize-the true impact of our mobile marketing investments. The ideal candidate has a passion for using data to shape mobile player acquisition and retention strategies, thrives in highly collaborative environments, and can translate complex analytical concepts into clear, actionable insights for partners across Blizzard. Responsibilities Build and maintain automated and dynamic predictive LTV models for mobile apps across multiple geographies, channels, campaigns, and platforms. Develop automated revenue and user growth forecasting systems that integrate with UA and finance workflows. Own the statistical framework for cohort modeling, retention projections, ROAS forecasting, and lifetime value prediction. Lead measurement strategy in a privacy-centric ecosystem, including: SKAdNetwork (SKAN) configuration and model-based postback interpretation Probabilistic attribution and MMM Incrementality testing and causal inference Funnel and cohort analysis across a complex landscape of iOS/Android/PC and Console Build data pipelines and automated reporting that harmonize deterministic and probabilistic signals. Collaborate with marketing, finance, and business teams to translate insights into actionable strategies by providing: Paid media performance insights Budget planning and scenario modeling, both one off and automated Creative testing analytics Channel-level optimization recommendations Build and maintain data pipelines and dashboards to monitor marketing KPIs and model outputs. Present findings and recommendations to stakeholders in a clear and compelling way. Stay informed on emerging trends and best practices in marketing analytics and data science. Requirements 8+ years of experience in data science, analytics, or a related field, with deep expertise in mobile marketing, predictive revenue modeling, or mobile UA analytics. Advanced degree (Master's or PhD) in Statistics, Applied Mathematics, Economics, Computer Science, or another quantitative discipline. Expert knowledge of: Cohort-based modeling and LTV prediction Marketing measurement frameworks (SKAN, ATT, MMM, incrementality) Paid media platforms: Meta, Google, TikTok, DSPs, SANs Probabilistic and deterministic attribution approaches, last-click attribution and alternatives Experience deploying models and working with engineering teams to automate workflows. Strong programming experience in Python (or R) and proficiency in SQL. Hands-on experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) and advanced statistical modeling techniques. Hands-on experience with modern data and analytics tools, including BigQuery/Snowflake, Airflow/dbt, Tableau/Looker, and Python-based ML frameworks (scikit-learn, TensorFlow, PyTorch). Expertise in data visualization and storytelling using Tableau, Power BI, Looker, or similar tools. Demonstrated ability to solve complex problems independently and lead cross-functional initiatives. Preferred Qualifications Hands-on experience with: MMPs (AppsFlyer, Adjust, Singular) SKAN 4 or 5 readiness and schema design Mobile data pipelines (event ingestion, postback processing) Knowledge of cloud platforms (AWS, GCP, Azure) and modern data engineering tools. Strong business acumen and the ability to influence senior leaders through compelling, data-driven insights. A passion for Blizzard games and for helping shape unforgettable mobile experiences through data craftsmanship. Your Platform Best known for iconic video game universes including Warcraft®, Overwatch®, Diablo®, and S