Netflix Interview Questions

Netflix is one of the leading media streaming services worldwide, delivering billions of hours of movie and TV show content to over 190 countries. The company has transformed the entertainment industry by rapidly developing innovative experiences for its creators and global audience.

As a company that creates and serves content, Netflix’s greatest priority is that consumers utilize their platform as much as possible. Netflix’s data team bridges the gap between consumer actions and business decisions through various ways, from delivering consumer feedback to creating recommendation algorithms.

In this guide, we’ll discuss the company’s interview process and common questions for each stage.

Netflix is an Internet subscription company that lets you stream and watch movies and TV shows

Netflix’s hiring process is carefully designed to evaluate a candidate’s expertise, past experiences, and alignment with company values. This includes:

1. Initial screening: Netflix’s first point of contact with prospective candidates is usually through a recruiter screening session to gauge qualifications, experience, and potential fit within the company.

2. Technical screenings: The next step is a telephone interview focused on technical skills. Led by an engineering manager or another team member, this stage dives into a candidate’s foundational skills and how they’ve applied them in real-world situations.

3. In-Person technical evaluation: After these virtual screenings, those who pass are invited for onsite interviews, which consist of two coding rounds:

   • Round 1 is a mix of medium to hard-level questions about algorithms and data structures.
   • Round 2 is where candidates are quizzed on both low-level and high-level design components.

   The onsite interview also allows interviewers to reassess a candidate’s cultural fit within the Netflix ecosystem.

4. Behavioral assessment: The final stage of this process focuses on a candidate’s soft skills, interpersonal dynamics, and problem-solving approach. This round is also an opportunity for candidates to reiterate their previous experiences, future goals, and how they see themselves contributing to Netflix’s vision.

From start to finish, the entire Netflix interview process can range from 2-4 weeks.

It’s important to note that Netflix significantly emphasizes core values and cultural fit. Being technically proficient is a significant advantage, but securing the role will ultimately require a strong understanding of the company’s ethos.

Netflix uses MySQL for billing, taxes, revenue, and tracking subscriptions. Having a solid foundation in SQL and interacting with relational databases is important for all Netflix data professionals. Here are some questions to try:

1. How can you find the percentage of user recommendations that originate from the same postal code as a page?

Imagine you’re working for a company that manages online page recommendations. The company has recently launched a new feature where pages can sponsor specific postal codes. The marketing team wants to understand the efficiency of this feature by identifying the percentage of users recommending a page that is from the same sponsored postal code.

To start, think about the relationships between the provided tables: page_sponsorships, recommendations, and users. How can you combine the tables to get the results you need?

2. Design a user recommendation system based on their friends’ liked pages.

Let’s say we want to build a naive recommender. We’re given two tables: one table called friends with user_id and friend_id columns representing each user’s friends, and another table called page_likes with a user_id and a page_id representing the page each user liked.

Write an SQL query to create a metric to recommend pages for each user based on recommendations from their friend’s liked pages.

Note: Do not recommend pages that the user already likes.

3. Determine whether each user has a subscription range that overlaps with another user’s completed range.

Given a table of product subscriptions with a subscription start and end date for each user, write a query that returns true or false for whether or not each user has a subscription date range that overlaps with any other completed subscription.

Completed subscriptions have end_date recorded.

Case study questions are an integral part of Netflix’s interview process. These interview questions cover system design, machine learning, and system architecture.

4. How would you design an ETL pipeline for a model that uses unstructured video data?

You’re designing an ETL pipeline for a model that uses videos as input. How would you approach collecting and aggregating this multimedia information, especially considering the unstructured nature of video data? If there are multiple potential methods, explain the tradeoffs.

5. How would you measure the success of a Netflix free trial?

Let’s say Netflix offers a subscription where customers can enroll for a 30-day free trial. After 30 days, customers will be automatically charged based on the package selected.

We want to measure the success of acquiring new users through the free trial. How can we measure acquisition success, and what metrics can we use?

6. How would you determine if a show is worth exclusive licensing?

Let’s say that you’re working at Netflix.

The company executives are working to renew a deal with another TV network that grants Netflix exclusive licensing to stream their hit TV series (think something like Friends or The Office). One of the executives wants to know how to approach this deal.

We know that the TV show has been on Netflix for a year already.

How would you approach valuing the benefit of keeping this show on Netflix?

To prepare for machine learning interview questions, we recommend taking the machine learning course.

Statistics and probability questions are among the most often asked topics in Netflix job interviews. Some questions to try include:

7. How would you explain the concept of a p-value to a non-technical person?

Make sure to describe statistical tests and hypotheses in your explanation.

8. How would you calculate the average lifetime value of a product?

You work for a SAAS company that charges $100 per month and has a 10% monthly churn rate, with the average customer staying for about 3.5 months.

Calculate the average lifetime value.

9. Compare and contrast MLE and MAP.

Be sure to describe the problems that can arise from each method.

To practice more of these questions, consider using the Statistics and A/B testing and the Probability learning paths. These resources will help you understand and solve complex problems effectively.

Netflix employs a range of algorithms, from recommendation engines to content delivery optimization. A strong foundation in algorithms and Python is crucial for data professionals at Netflix.

10. Find the median from a stream of data.

You have an ordered list of integers and a novel integer that hasn’t been inserted. Y

How can you compute the new median after this new integer is included?

Remember: the median in an ordered list is the central value. If the list has an even count, there’s no sole middle value, and the median is the mean of the two middle values.

11. How can you rotate an array filled with random values?

Given an array filled with random values, write a function rotate_matrix to rotate the array by 90 degrees in the clockwise direction.

To start this problem, consider if there’s anything special about this array that could guide your approach to the problem.

12. How would you implement a priority queue using a linked list?

Priority queues are important data structures used to enqueue items with an attached priority. While typically implemented with a heap, implement a priority queue using a linked list that supports the following operations:

• insert(element, priority): This operation should be able to insert an element into the Priority Queue, along with its corresponding priority.
• delete(): This operation should remove and return the element with the highest priority. If multiple elements share the same highest priority, the element first enqueued should be returned. If the queue is empty, return None.
• peek(): This operation should return the element with the highest priority without removing it from the Priority Queue. Again, in the case of equal highest priorities, the element first enqueued should be returned. If the queue is empty, return None.

To guide your thought process, consider the following:

• Given the inherently sequential nature of linked lists, what insertion strategy would be optimal to ensure the efficiency of the delete operation?
• Would a sorted linked list be the most beneficial? Are there better alternative structures (like doubly-linked lists)?
• Handling edge cases is crucial. How would you address scenarios like duplicate priorities or operations on an already empty queue?

To practice coding interview questions, check out the Python learning path or the full list of Algorithms questions in our database.

Practice for the Netflix interview with these recently asked interview questions.