Lead end-to-end ML lifecycle work: prototype, deploy, automate, and monitor production models on GCP. Drive MLOps adoption, build Vertex AI pipelines, implement CI/CD and containerized deployments, partner with product and trading teams, design experiments and monitoring, and mentor other data scientists to deliver measurable business impact in areas like trading, fraud, personalization, and responsible gaming.

Lead and grow a US-based data science team while remaining hands-on: design, build, deploy, and maintain production ML models; write code; implement MLOps on GCP/Vertex AI; mentor junior data scientists and ML engineers; establish workflows, standards, and code repositories; translate business problems into rapid, production-grade data science solutions.