Netflix Data Scientist interview questions tend to emphasize practical impact over algorithmic puzzles: expect medium-to-hard SQL and Python on real data problems, rigorous experimentation and metrics design, product sense for viewer-facing features, and applied modeling for personalization teams. What’s distinctive is Netflix’s strong focus on ownership and business impact—interviewers probe how you defined success, measured lift, and shipped solutions end-to-end. You should also expect a heavy behavioral/culture component that tests whether you can thrive with high freedom and accountability. For interview preparation, prioritize hands-on practice: timed SQL problems with sessionization and cohort analysis, clear explanations of A/B test design and power trade-offs, crisp product-case narratives tying metrics to business decisions, and condensed stories that show ownership and learning. For senior roles add data-system or experimentation-platform design. Simulate full loops, practice thinking aloud, and quantify past impact on your resume and in answers so you can demonstrate both technical depth and measurable outcomes during the on‑site.