Data Scientist 5 - Ads Experimentation

Netflix•New York, NY

2d•$372,000 - $600,000

About The Position

The Ads Data Science & Engineering team is responsible for the foundational logic of the Netflix ads business. We develop the analyses, tools, and predictive algorithms that drive member joy and advertiser value. As a Data Scientist in this 0–1 space, you will not just execute tasks; you will be a primary architect of our experimentation roadmap, helping us navigate the transition from a nascent offering to a sophisticated global marketplace.

Requirements

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.
A self-starter who thrives in an environment of radical transparency and high autonomy. You are a mentor and a collaborator who prioritizes the inclusion of diverse perspectives to reach the best possible decisions.

Responsibilities

Design and execute rigorous experimental frameworks, leading 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.
Drive the advancement and implementation of biddable media models and dynamically priced auctions, developing strategies to optimize marketplace mechanics, ensuring balance between supply, demand, and member experience.
Partner with Product and Engineering to solve "cold-start" measurement challenges and rapidly scale our ad platform across diverse international markets.
Act as a high-level consultant to Product, Strategy, and Engineering teams, autonomously identifying research opportunities, quantifying their potential business impact, and advocating for resource allocation to pursue them.
Cultivate strong partnerships with cross-functional stakeholders including product, engineering, operations, design, and consumer research.
Deliver end-to-end solutions using advanced causal inference, machine learning, and data exploration, maintaining a high bar for documentation and reproducibility.