(Transcript)

tl;dr

Every interview will almost surely include a variation of “Why our company?” Whether it be “Why do you want to work here?” Or “Why are you a good fit?” Or any other variation.

A question which seems simple on its surface, if approached naively, can expose you as being unprepared, too-junior, or both.

The question beneath the question

A literal interpretation of “Why Netflix?” is “Why do you want to work at Netflix?” It’s harmful to approach the question in this way. Instead, interpret it as “What do you know about Netflix and how can you help?”

When you answer the question literally you are effectively saying “Here’s how Netflix can help me”–”I’m such a fan,” “I’m so passionate about this space”–when you should be doing the opposite–showing them how you can help Netflix! To do that, tell them a brief compelling story which connects what you know about them to what you can do for them.

Let’s go through Good, bad, and ugly example answers, starting with the worst and working our way up. For all of these examples, let’s assume the candidate is interviewing for a senior machine learning engineering position at Netflix.

Ugly

“That's a great question. I want to work at Netflix because I have always been passionate about accessible products that have as big of an impact as possible, just like how Netflix's mission is to entertain the world.”

Why it’s ugly

• Ugly answers are ugly because they’re all about “me, me, me.”
• It’s literally answering the question of “Why do you want to work at Netflix?”
• It adds nothing to the company’s valuation of the candidate’s skillset; there’s no demonstration of the candidate having done their homework, and no tying in of the candidate’s skillset

Bad

“I believe that Netflix’s cutting-edge technology, driven culture, and unique structure make it an ideal place to grow professionally and make an impact. I am also passionate about being part of a team that is constantly pushing boundaries and creating compelling content for viewers around the world. There is so much expertise in machine learning at Netflix, and the team members are very impressive. My background in casual inference fits quite well, and I’m confident I can make an impact quickly.”

Why it’s bad

• Bad answers are bad because they are all about “you, you, you.”
• This answer is attempting to answer the question beneath the question (which is better than answering the question literally) but it’s not successfully doing so. It’s telling and not showing: for doing research on this opportunity and tying in how the candidate can help.
• There’s no inclusion of metrics/impact, or scope of current role to score any points relevant to a senior position.

Good

I recently read a research article Netflix put out called “Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments” and was energized by the research and findings. Specifically, I appreciate the inclusion of offline reinforcement learning methods.

You and I both know that it won’t be A/B test that gets the Netflix algorithms to reach their full potential, it’s going to be causal inference which does that. On the Netflix website, the company describes itself as a “pioneer of causal inference.” So, Netflix needs smart, independent ML engineers who are skilled in causal inference to continue to lead the entertainment industry.

My expertise within machine learning is in casual inference. My current role, where I lead a team of 4-5 ML engineers, is highlighted by running causal inference tests and presenting findings to CMOs, VPs, and technical audiences. These casual inference tests have generated over 10 million dollars in annual revenue, mainly in the area of target advertising.

Netflix would be a solid match for my skillset, and I’d appreciate the opportunity to further my expertise in causal inference.

Why it’s good

• Good answers are good because they tell a story which unites you and me.
• Demonstration that the candidate did their homework
• Clearly adding value to the company’s impression of the candidate
• Metrics and impact included
• Senior-scope points mentioned

Key takeaways

From now on when you hear “Why Netflix, or Why Google or why any other company, don’t hear that question. Hear the question beneath the question: “What do you know about us and how can you help?” Answer that question instead, tell them a brief compelling story which connects what you know about them to what you can do for them.