Applied Scientist

WHAT YOU’LL DO

Viant’s Machine Learning team is building autonomous advertising systems that make real-time decisions across targeting, ad optimization, bidding, measurement, and personalization. These systems process hundreds of millions of events daily and operate in the high-throughput, low-latency environment of programmatic advertising.

As an Applied Scientist, you will apply reinforcement learning and related decision-making methods to improve how Viant selects, ranks, and bids on advertising opportunities. You will work across contextual bandits, exploration and exploitation, counterfactual learning, and model-based experimentation to turn research into production systems that improve campaign performance, auction efficiency, and measurable business outcomes.

THE DAY-TO-DAY

•  Develop, train, and evaluate reinforcement learning, contextual bandit, ranking, and prediction models for ad optimization, bid optimization, targeting, and personalization.
• Study auction dynamics, delayed feedback, exploration and exploitation, budget constraints, pacing, and reward design to improve real-time advertising decisions.
• Translate research ideas into production-ready models that operate reliably at high throughput and low latency across Viant’s advertising platfor