The interview process takes 2-4 weeks on average.

• Stage 1: Initial phone screen by HR.
  
• Stage 2: A phone interview with the hiring manager
  
• Stage 3: An onsite interview composed of two parts: the first is with 4 data scientists/engineers and the second is with 3 higher level execs. The questions are a mix of product, business, analytical and stats questions. Stats questions mostly revolve around A/B testing: hypothesis testing, etc. There can be some easy-medium SQL questions. Analytical questions include a hypothetical problem to analyze, metrics to evaluate product performance, etc. Higher level executives mostly focus mostly on background and past experience.

• Q 1: How would you design an experiment for a new feature we're thinking about. What metrics would matter?
• Q 2: Given a month's worth of login data from Netflix such as account_id, device_id, and metadata concerning payments, how would you detect fraud? (identity theft, payment fraud, etc.)
• Q 3: Given a single day with a large sample size and a significant test result, would you end the experiment?
• Q 4: How do you know if one algorithm is better than other?
• Q 5: How do you prevent overfitting and complexity of a model?
• Q 6: How do you measure and compare models?
• Q 7: How should we approach attribution modeling to measure marketing effectiveness?
• Q 8: How would you build and test a metric to compare two user's ranked lists of movie/tv show preferences?
• Q 9: What are the differences between L1 and L2 regularization, Why don't people use L0.5 regularization for instance?
• Q 10: Why Rectified Linear Unit is a good activation function etc.
• Q 11: When you split a population for A/B testing, what are some reasons you could see a significant difference in the control and variant groups?

We promise our customers stellar service, our suppliers a valuable partner, our investors the prospects of sustained profitable growth, and our employees the allure of huge impact

- Becoming the best global entertainment distribution service- Licensing entertainment content around the world- Creating markets that are accessible to film makers- Helping content creators around the world to find a global audience