Staff Applied Scientist

Responsibilities

• Build and maintain control systems that dynamically allocate ad budgets across sell-side partners based on quality signals and performance targets.
• Design and analyze experiments using causal inference methods to measure the impact of inventory decisions on advertiser KPIs.
• Develop recommendation systems and curation frameworks to help buyers find supply that reaches target audiences at scale.
• Create time series models to anticipate supply volume shifts for better planning.
• Partner with engineering, product, and business teams to translate research into scalable, production-ready systems.
• Define the applied science roadmap by identifying high-impact problems and driving projects from research through production.

Requirements

• Advanced degree (PhD preferred) in Data Science, Statistics, Machine Learning, Economics, Math, or Computer Science.
• 7+ years of experience in data science, or 5+ years of experience if holding a PhD.
• Proven track record of owning projects end-to-end, from initial research to large-scale productionization.
• Strong expertise in machine learning, statistics, experimental design, and causal inference.
• Experience developing recommendation systems or ranking models.
• Proficiency with large-scale data processing tools such as Spark, EMR, or Databricks.
• Strong software engineering fundamentals, including clean code, version control, and code review practices.

Preferred Qualifications

• Experience in programmatic advertising, real-time auctions, or supply-side systems.
• Familiarity with control theory, constrained optimization, or budget allocation systems.
• Experience building or applying agentic AI workflows, including the use of LLMs for automation or decision support.

About the Company

The Trade Desk is a global technology company and the world’s leading independent platform for digital advertising. Our technology helps advertisers reach the right audiences across the open internet—from streaming TV and podcasts to mobile apps and news. We solve massive technical challenges, processing enormous datasets in real time to power the global digital advertising marketplace.