Staff Applied Scientist , Inventory & Marketplace Quality

The Trade Desk The Trade Desk · Media · Bellevue, WA · Data Science

Staff Applied Scientist role focused on building and productionizing statistical and machine learning models for fraud detection, invalid traffic, and inventory quality in the digital advertising marketplace. The role involves technical ownership of the data science roadmap, designing and deploying models, defining metrics, and developing analytical frameworks. It also requires cross-functional collaboration with engineering and product teams, and leadership/mentorship of other data scientists. The position emphasizes end-to-end project ownership in adversarial, large-scale environments.

What you'd actually do

  1. Own the data science vision and roadmap for MQE initiatives, aligning technical direction with strategic goals and industry trends.
  2. Design, build, and productionize statistical and machine learning models to detect fraud, invalid traffic, and low-quality inventory in adversarial, large-scale environments.
  3. Define and maintain metrics, experimentation procedures, and monitoring systems to ensure long-term performance.
  4. Develop analytical and explainability frameworks that provide clear visibility into how quality initiatives impact inventory supply, advertiser spend, and marketplace dynamics.
  5. Collaborate with product and business stakeholders to translate analytical insights into clear, defensible decisions and marketplace enforcement strategies.

Skills

Required

  • Advanced degree (MS or PhD) in a quantitative field such as Statistics, Computer Science, Economics, Applied Math, Operations Research, or similar.
  • 7+ years of experience working in a DS role that involves bringing products from ideation to production.
  • Deep expertise in statistical modeling, machine learning, and large-scale data analysis.
  • Strong understanding of experimentation, causal inference, and metric design in complex systems.
  • Familiarity with large-scale data and ML tooling (e.g. Spark, distributed training, real-time inference systems).
  • Proven ability to lead ambiguous, high-impact projects end-to-end as a senior individual contributor.
  • Excellent communication skills and the ability to influence across organizational boundaries.

Nice to have

  • Experience in programmatic advertising and/or real-time auctions is a plus.
  • Track record of mentoring senior data scientists and shaping team-level technical direction is a plus.

What the JD emphasized

  • productionize
  • large-scale environments
  • monitoring systems
  • explainability frameworks
  • marketplace enforcement strategies
  • adversarial
  • end-to-end

Other signals

  • detect and prevent fraud
  • measure and improve inventory quality
  • optimize marketplace dynamics
  • statistical and machine learning models
  • large-scale data analysis