Interview Guide May 02
May 023 rounds
One of the main responsibilities of a Netflix Data Scientist is to analyze large sets of data to understand customer behavior and preferences. This includes analyzing viewing patterns, search queries, and other interactions with the platform. Using this information, they are able to identify trends and make recommendations to improve the customer experience, such as by suggesting new content or by improving the recommendation algorithm.
Another important responsibility of a Netflix data scientist is to develop and implement A/B tests to optimize various aspects of the platform. This could include testing different layouts, features, or pricing plans to see which perform best. They also develop machine learning models to understand and predict user behavior, and use this information to optimize their experience.
Netflix also focuses on using computer vision and machine learning approaches to solve high-impact problems in Studio including virtual production, VFX, post production, and animation.
Netflix hires Data Scientists across the company and there are different seniority levels depending on the scope and expected impact. They have Senior level roles and some openings for Data Science Managers. Netflix has a variety of data science positions available, including: ML Engineer, Applied Research Scientists, Data Analysts and BI Engineer.
It's worth noting that the names of the positions and their responsibilities may vary depending on the region and the specific team.
How to Apply for a Data Scientist Job at Netflix?
To apply for a Data Scientist job at Netflix, go to the Netflix’s career website and search for data scientist roles. You can also check other job search websites, such as LinkedIn or Glassdoor, to see if there are any open positions. Carefully read through the job description and requirements to make sure you meet the qualifications and that the role aligns with your interests and experience. Once you have found a position that you are interested in, you will be able to submit an application online. However, we would highly recommend taking the referral route if you know someone in the company as it increases your chances meaningfully. Having said that - Netflix currently doesn’t give its employees referral bonuses. So employees only refer people if they actually know them really well and are confident they’ll thrive at Netflix (it reflects really badly on them if a referred employee under-performs. In this context - it can often be challenging to find an internal referrer, making it all the more important that your resume be capable of “standing out” by itself. A tip we had regarding your resume - make a few tweaks for the position and the role you are applying for which will help you have a better chance compared to other candidates. If you're not sure how to do that, Prepfully offers a resume review service, where actual Netflix recruiters will give you feedback on your resume.
As a part of the Netflix Data Scientist interview, you will need to go through multiple interview rounds:
1. Phone screening rounds - The initial phone screening rounds usually consist of two rounds - one phone interview with the recruiter and another with the Hiring Manager. The questions here will be about your work experiences and the roles you’ve had in the past company.
2. Technical Phone Screening or Onsite Technical Interview - Candidates reported being interviewed by multiple people, usually data scientists or data engineers. The interview is conducted meeting these people one on one. A mix of product, business, analytical and statistical questions are asked in this round along with a few SQL questions.
3. Onsite Interview - In this round, you will face multiple higher executives. This round is mostly focused on background and past experience.
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The initial phone screening rounds usually consist of two rounds - one phone interview with the recruiter and another with the Hiring Manager. The first round with the recruiter will focus on the culture fit and behavioral type of problems. The second round with the Hiring Manager will be mainly focused on your management experience. Netflix heavily focuses on their culture and what they want to achieve so we’d recommend preparing for these rounds accordingly.
- Why do you want to join Netflix?
- Why do you think you will be a good fit for the role?
- What responsibilities do you expect to have from your job at Netflix?
- Tell us more about your management experience.
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The second round can either be a technical phone screening or an onsite technical interview. Candidates reported both of these rounds to be similar with the questions and the structure being almost the same. Here you will face multiple data scientists and data engineers one on one. A mix of product, business, analytical and statistical questions are asked in this round along with a few SQL questions. Statistical questions will mostly revolve around A/B testing, Hypothesis Testing and Causal Inference. Analytical questions will include a hypothetical problem to analyze, for instance - metrics to evaluate product performance. Some candidates also reported being asked several machine learning questions.
- What are the basic assumptions of A/B testing? Do you have experience in A/B testing?
- 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?
- Given a single day with a large sample size and a significant test result, would you end the experiment?
- How do you know if one algorithm is better than the other?
- How would you use ANOVA to determine if there is a significant difference in the mean satisfaction levels among customers from different regions?
- How would you use a simple join to combine data from two tables?
- How would you design an experiment for a new feature we're thinking about. What metrics would matter?
- Explain p-value.
- Can you explain the concept of causal inference and give an example of its application in a real-world scenario?
- Can you provide an example of a real-world application of dimensionality reduction techniques and how they were used?
- Can you discuss a time when you had to handle imbalanced data in a machine learning model? How did you approach the problem?
- Can you explain the concept of overfitting and how to avoid it in a machine learning model?
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The third round is an onsite interview with higher executives from Netflix. This round is mostly focused on your background and past experience. The questions here won’t be technically tough but here you will have to explain some technical concepts.to a non-technical executive. There will be heavy emphasis on the culture at Netflix and you will be asked about what you want to achieve by working at Netflix. The goal is to check your alignment with their values.
- What are the most important metrics for Netflix?
- How do you measure revenue and cost?
- How do you capture customer satisfaction when there is a lack of survey responses?
- How do you measure customer engagement and disengagement?
- Can you describe a situation where you had to adapt to a new technology or tool to complete a project?
- Can you describe a situation where you had to communicate your findings to a non-technical team?
When you are preparing for a Netflix Data Science interview - we’d recommend the following things to keep in mind:
- Read about the expectations Netflix has from their employees. This will help you align your answers with their culture fit.
- Refresh your fundamentals and be prepared to think. Netflix tends to ask open ended questions. Think about the business need in addition to the technical task.
- The most important tip to get through the behavioral questions would be showing your passion for TV and movies and your interest in defining the future of entertainment.
- Highlight your proficiency in at least one of the following - Java, Python or Scala.
- Make sure you are comfortable with complex SQL queries and able to analyze large sets of data.
Responsibilities of a Data Scientist at Netflix
The responsibilities of a data scientist at Netflix across roles can broadly be seen as-
- Engineer efficient, adaptable and scalable data pipelines to process structured and unstructured data. For example, create a data pipeline that can ingest raw data from multiple sources and transform it into an organized data set.
- Provide technical vision and strategy for building a data ecosystem that enables Netflix to leverage data within cross-functional teams.
- Work with senior management and executives to develop the vision for a data-driven Netflix Studio. For example, strategize how studio production can be streamlined with data-driven insights.
- Partner closely with business stakeholders and engineering teams to integrate work outputs into the production workflow.
- Provide thought leadership and identify new areas where Machine Learning (ML) can play a significant role. For example, analyze existing data sets and identify opportunities where ML can be applied to generate insights.
Skills and Qualifications needed for Data Scientists at Netflix
Some of the skills and qualifications that may be required for a Data Scientist at Netflix include:
- Make sure you are comfortable with complex SQL queries and able to analyze large sets of data. For instance - if you’re in a viewer experience team; you’ll have a lot of data points on what people watch, when, and granular data points on how much time they spend, so there’s a lot to analyze
- Showcase your expertise in engineering data pipelines using big data technologies such as Hive, Presto, Spark, and Flink on large scale data sets through your previous work experience.
- Demonstrate your conceptual understanding of AWS cloud resources such as S3, EC2, and RDS.
- Highlight your proficiency in at least one of the following - Java, Python or Scala with at least 5 years of software/data engineering experience.
- Show your passion for TV and movies and your interest in defining the future of entertainment. Netflix wants to get people who care about the industry - so if you can think of ways to get this across, you’ll have an advantage!
The salary range for a Data Scientist at Netflix would depend on several factors such as the person's experience, location, and the specific role they are hired for. However, the average salary for a Data Scientist at Netflix is approximately $140,000 to $165,000 per year, with top earners making over $180,000 per year. Keep in mind that these figures are just rough estimates and the actual salary could be higher or lower based on the specific factors mentioned earlier.
The interview process for a Data Scientist role at Netflix typically includes 3 primary rounds - the phone screening rounds, a technical phone screen or onsite technical interview, and the final onsite interview round. The initial phone screening rounds usually consist of two rounds - one phone interview with the recruiter and another with the Hiring Manager. The second round can either be a technical phone screening or an onsite technical interview where you will face multiple data scientists and data engineers one on one. The final onsite interview will be with multiple higher executives. This round will be mostly focused on your background and past experience.