• Lead the design, development, and deployment of ML models that predict and influence customer behavior — including churn, retention, activation, lifetime value, and lifecycle transitions. • Build behavioral segmentation frameworks, uplift models, and propensity scoring used across product, lifecycle marketing, and account strategy. • Drive insights for core product areas (audience targeting, measurement, bidding, onboarding, campaign performance) using a mix of causal inference, predictive modeling, and experimentation. • Own end-to-end analytics for key initiatives: partner with Product to define success metrics, guide instrumentation, design experiments, and quantify impact. • Design, build and deploy rigorous and statistically sound models and systems that help customers understand causal effects of their marketing strategies. • Influence product roadmaps using quantified opportunity sizing, behavioral funnel analysis, and deep dives into customer usage patterns. • Collaborate with Data Engineering and ML Platform teams to build scalable pipelines, datasets, and model operationalization workflows. • Act as a technical mentor for the broader analytics and data science team; elevate scientific rigor, model quality, and best practices.