Data Scientist 4/5 - Identity DSE

Benefits

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Family-building benefits

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Not verified last checked Jun 13, 2026

Salary

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401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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About this role

Data Scientist 4/5 - Identity DSE USA - Remote 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. Our Commerce Data Science team works with a broad range of collaborators and stakeholders, including Product, Engineering, and Finance, to inform commerce strategy and data-informed decision-making through analysis, metrics research, experimentation, causal inference, and modeling, but also through exceptional judgment, partnership, and business acumen. As part of our investment in next-generation commerce and identity capabilities, the Identity team is responsible for building a unified, individual-level identity platform that will serve as the core foundation for future product experiences. This cross-functional, cross-domain effort will reshape how we understand our users and how identity signals are captured, connected, and used across the Netflix ecosystem. Our mission is to deliver a more consistent, accurate, and personalized experience for every individual who interacts with Netflix. We are hiring founding data scientists to help define this space from the ground up and develop the scientific frameworks that will power new commerce experiences at global scale. As a Data Scientist, you will join a team of other stunning Data Scientists, Analytics Engineers, Machine Learning Scientists, and Research Engineers. You will use data to identify opportunities and help shape

Read the full description at explore.jobs.netflix.net. FewerJobs shows a source-linked preview and links to the original posting.