Lead design and production deployment of end-to-end ML models (PQL scoring, churn, expansion) using MLOps. Build pipelines for dataset/versioning, monitoring, automated retraining, and model registry. Collaborate with Product, Sales, and Data Engineering, own model observability, incident response, dbt data models, and experimentation lifecycle to deliver production-grade analytics.

Design and scale end-to-end data architecture and real-time/batch pipelines to unify product telemetry, CRM, and billing into a single source of truth. Build data foundations for ML (feature pipelines, training datasets, low-latency scoring), define telemetry/event contracts, implement data quality, monitoring, governance, and enable self-service analytics.

The Senior Data Scientist will engineer Zoom's Revenue Intelligence Engine, developing scalable systems for lead scoring and churn prediction while collaborating with various teams to provide data-driven insights.