Data Scientist 5 - Ads Experimentation

Netflix Netflix · Big Tech · United States · Remote · Data & Insights

This role focuses on designing and executing experimental frameworks for Netflix's ads business, developing predictive algorithms, and optimizing marketplace dynamics. It involves transitioning from manual analysis to scalable, automated solutions and applying advanced causal inference and machine learning techniques to drive business decisions and global expansion. The role is considered AI-related due to the use of ML and causal inference, but the primary output is an experimentation platform and business insights rather than core AI model development.

What you'd actually do

  1. Design and execute rigorous experimental frameworks. You will lead the transition from manual analysis to automated, scalable solutions integrated with the Netflix Experimentation Platform, defining best practices that ensure trustworthy decision-making at scale.
  2. Drive the advancement and implementation of biddable media models and dynamically priced auctions. You will develop strategies to optimize marketplace mechanics, ensuring balance between supply, demand, and member experience.
  3. Partner with Product and Engineering to solve "cold-start" measurement challenges and rapidly scale our ad platform across diverse international markets.
  4. Act as a high-level consultant to Product, Strategy, and Engineering teams. You will autonomously identify research opportunities, quantify their potential business impact, and advocate for resource allocation to pursue them.
  5. Deliver end-to-end solutions using advanced causal inference, machine learning, and data exploration, maintaining a high bar for documentation and reproducibility.

Skills

Required

  • MS or PhD in a quantitative field (e.g., Statistics, Economics, Mathematics) or equivalent practical experience
  • Significant experience with auction dynamics, yield management, or supply-demand matching within a marketplace setting
  • Mastery of causal inference and experimental design, with specific experience solving for interference and network effects in marketplace environments
  • Expert proficiency in Python or R, and advanced SQL
  • Ability to translate complex statistical results into actionable business narratives for stakeholders at all levels of the organization
  • Self-starter who thrives in an environment of radical transparency and high autonomy

Nice to have

  • mentor and a collaborator who prioritizes the inclusion of diverse perspectives

What the JD emphasized

  • lead the transition from manual analysis to automated, scalable solutions
  • advanced causal inference, machine learning, and data exploration
  • auction dynamics, yield management, or supply-demand matching within a marketplace setting
  • experimental design, with specific experience solving for interference and network effects in marketplace environments