Leads the end-to-end design, deployment, and performance of real-time ML prediction and bid-optimization systems for programmatic advertising. Provides hands-on technical leadership to applied scientists and ML engineers, formulates optimization problems, manages production ML challenges such as latency, delayed feedback, drift, and retraining, and aligns technical roadmaps with business priorities.

Develop and productionize reinforcement learning, contextual bandit, ranking, and prediction models for real-time advertising optimization. Analyze auction dynamics, experimentation, counterfactual evaluation, and large-scale data to improve bidding, targeting, personalization, and campaign outcomes. Collaborate with engineering, science, and product teams to deploy, monitor, retrain, and evaluate high-throughput, low-latency models.