Job Description
At Netflix , our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. The Team Netflix 's ability to invest in the content that entertains hundreds of millions of members - billions of dollars each year across film, series, games, and live experiences - depends on getting subscription pricing right. Effective pricing generates the sustainable revenue that funds Netflix 's next slate of ambitious content. The Subscription Revenue DSE team brings rigorous measurement and modeling to that challenge. We are a small, focused group of data practitioners who partner with Finance & Strategy, Product, and Consumer Insights to understand how pricing actions actually impact member behavior globally. Our work spans causal measurement of pricing impacts, elasticity, and willingness-to-pay research, and execution analytics. We own and continuously evolve the tools that give Netflix a clear-eyed, evidence-based view of what its pricing decisions actually achieve. The Role We are looking for a Machine Learning Scientist to join our team and bring deep ML and causal inference rigor to some of the hardest quantitative problems in subscription pricing. You will collaborate with other researchers to advance our causal measurement capabilities, own complex ML initiatives end-to-end, and bring deep technical rigor to some of the hardest quantitative problems in subscription pricing. You will also partner with Finance & Strategy leaders and Product managers, translating complex modeling work into clear, actionable insights that drive significant business decisions. What You Will Do Design and implement quasi-experimental and causal inference approaches (difference-in-differences, synthet
