Amazon UX Researcher Interview Guide

The Amazon UX Researcher interview process typically looks like this:

1. Online assessment (some applicants)
2. Recruiter screen
3. Phone screen
4. Writing sample & interview (some loops)
5. Onsite loop: 
   Portfolio Review 
   Research Planning Exercise
   Behavioral interviews 
   Bar Raiser 
6. Debrief, team matching and offer

Prepfully candidates say the average time for hire lies at 35 days.

Before we get into the round-by-round description, you should know that Amazon structures its entire operational culture around its 16 core Leadership Principles (LPs). Each interviewer/ round in the loop will be explicitly assigned to evaluate about 2-3 of these.

Some applicants are asked to fill out an online assessment that can be of 2 types:

• Work-style assessment: Takes 10-20 minutes and asks you to choose statements that best describe your workstyle. These questions are strongly anchored to the LPs so the culture screen starts this early in the loop. 
• Work sample simulation: a mini trial by fire that takes 30-60 minutes that features practical tasks like reading charts or making LP-driven decisions.

You don’t really need to prepare in advance for this but you have to be sure to submit it before the deadline passes.

This is a 30-45 minute phone/video conversation with a recruiter or sometimes with the HM. Amazon clarifies that this is a formal interview that’ll screen and understand your basic qualifications and technical background. You might face a couple of behavioral questions that are tied to the LPs. At the end, you’ll have time for your own questions about the role/ team. 

Prepare to answer questions like:

• Tell me about yourself. Why are you applying to Amazon? 
• What are you currently working on day-to-day? 
• What kind of compensation are you expecting?

From this point on, the recruiter is your main POC so you should take the time to clarify which subjects/ skills your interviews will focus on, especially if you’re interviewing to be a quant-focused researcher. There are a few discrepancies about whether a separate coding round or statistics round exists for these roles and your recruiter is the best person who can confirm. 

Prepare a short answer to “tell me about yourself” that’s built around a highlight of your current role and has a segue into the opportunities at Amazon that excite you. 

You’ll face 1-2 60-minute calls with the Hiring Manager or another senior leader and they’re positioned as the gatekeeper to the onsite interviews. You’ll face a mix of any of these formats:

• Behavioral screen: The HM will begin with questions about your background and your motivation for joining Amazon. The rest of the screen will be rooted in LP-focused questions to assess your culture fit. 
• Research skills screen: Expect a deep-dive on your research background and the methods you’ve used. It’ll usually take the shape of a retro where interviewers ask direct methods questions and dig into a specific project in detail - including how the team used what you produced. 
• Portfolio screen: Some UX teams that run 2 phone screens use the first for LPs and the second to examine the portfolio you submitted while applying. 

Some teams add role-specific exercises at this stage and if that’s the case, your recruiter will let you know beforehand. 

Candidates have reported the following questions:

• Tell me about a time where you had multiple options for a solution. How did you decide the perfect fit?
• Tell me about a time you took a risk. Did it pay off?
• How do you use data to develop strategies and get buy-in from teammates?
• How is the output of tree testing different from card sorting?
• Describe a project where you used personas. 
• Have you ever been in a position to advocate a product?

If this step in the interview process applies to you, you’ll be asked to submit a written case study of one of your past research studies ahead of a 60-minute retro. 

You’ll be asked to go into details like what the setup was, your challenge specifically, how you went about solving it and what outcomes you can put numbers to (exactly like the STAR framework).

Doc:

You’ll be expected to submit a plain text doc with no embedded charts or images because the whole assignment plans to evaluate how well you structure your complex logic in writing. This is exactly how Amazon works internally, where teams write docs instead of building slide decks to pitch their decisions.

One of our coaches who was actively hiring UX Researchers at Amazon over the last few years says they use the following rubric to evaluate writing samples:

• Clarity of thought
• Content and development
• Organization
• Language use
• Voice and style

They said that the writing sample is graded at a high level against the Amazon-wide bar and you’re expected to describe your research in a way anyone in the company can understand. 

The writing sample is also assessed through the LP-lens, especially against:

• Are Right, A Lot
• Deliver Results
• Dive Deep

Interview:

Our coaches say that interviewers typically open with clarifying questions about anything they didn’t follow in the write-up (e.g. exactly who was involved). Then, in a typical retro style, they’ll get into questions about your method and expect you to defend your choices. 

The questions will be tied closely to what you wrote so be prepared for a line of questioning that’s along the lines of: 

• Why did you choose to write about this particular project?
• Talk me through why you designed the research the way you did.
• What were the pros and cons of your approach?
• Were there other methods you considered?
• How did you approach analysis? Talk me through exactly what you did with all the data you collected.
• Looking back, would you have done anything differently? What if you had more/less time? What if you had a bigger budget?
• Was there any pushback on your approach from stakeholders? 

Being wary of AI-generated content is the latest sport in the interview landscape so expect the interviewer to sanity check the doc for evidence that you wrote it yourself. You absolutely must use AI for the research and structuring but NOT use it to write out the content. Using AI for research and analysis is an efficiency advantage that you can’t afford to deny but if your doc has jarring ai-isms especially in presentation/writing style, the interviewer will be upset. 

So please don’t insult your interviewer’s sharp eye with a one-prompt generated doc. 

Some more tips from our coaches for the writing assessment:

• Write about a study that’s completed so you can speak to its impact
• Relate the user’s problem to the overall business
• Say what tipped you toward the method you chose, be it budget or directional feedback
• If a metric was calculated by a data scientist or another partner team, say so and explain how it fed into your research or how you checked it. 
• During the interview, give the short answer/summary and then offer to go into the explanation. The interviewer will have a laundry list of questions to ask and spending too long on one will cramp the round. 

During the onsite, you’ll face the following rounds that run for 60 minutes each:

• Portfolio Review 
• Research Planning Exercise
• Behavioral interviews 
• Bar Raiser 

Candidates report an onsite of 5-6 rounds which hints at multiple rounds of the same topic (usually 3-4 behavioral). Your interviewers for the onsite will be UX professionals, PMs, SDMs and business partners from the team you’re applying to and from other teams. 

This is a presentation round in which you walk the interviewer through your research case studies and answer their questions about your methods and your impact. Amazon recommends that you come prepared with 3 detailed case studies that exhibit the depth and breadth of your work. 

For each case study, you should have a crisp narrative that touches upon:

• the customer problem you were trying to solve, and why you were solving it
• brief context on the product space
• your own role and contribution 
• the impact you and the project made, backed by numbers

Candidates say that the follow up questions went deep into method and how the team used the research after. Even during mocks for this round, our coaches are sure to ask questions like:

• Was there any downside to the method you chose?
• Why did you choose this number of participants?
• Did your qualitative findings and the quantitative data disagree?
• What decision would the team have made without your research?

It’s incredibly important to tie your work back to the impact you had on the product or business you were aiming to help make better decisions around. One of the most common issues our coaches report is that UXR candidates wrap up with a very robust analysis of their own work, but miss talking through the specific decision they influenced, its cascading impact on the business, and the metrics they ended up moving as a consequence.

This is a session in which the interviewer (a researcher) plays stakeholder with a research request and you scope the problem and propose how you’d study it. The prompt/scenario is a UX problem unrelated to Amazon, which spares you from critiquing your interviewer’s product to their face. The entire round is conducted verbally, without even so much as a whiteboard. 

The exercise is a test of your process and isn’t some kind of brainteaser. The interviewer will keenly pay attention to:

• Your process for assessing a research challenge
• How you work through ambiguity and how to shape it
• How you respond to roadblocks or new information/constraints

That last point should prepare you for the fact that interviewers can interject your study partway with new information just to see how you pivot on a dime.

The prompts can be something like

• I run a meal-prep subscription and we’re thinking of launching a vegan plan. I need to know if there’s demand for it and what I should include in it. 
• We’re a fitness tracker app that’s planning to expand internationally into Japan and Brazil next quarter. What do we need to know before we localize the app?

Before you wrap up, you should proactively check if your plan meets what the stakeholder/interviewer asked of you and talk about how you’d measure success over time. If it doesn’t meet the expectations, you should say so honestly and explain how things would change if you had more time. 

You will for certain be presented with theoretical curveballs (think “you’ve been told this survey will clash with another that’s going out at the same time at an org level; what will you do now?” or “The team’s PM wants to use the same research call to also get insight on an adjacent product experience they’d been mulling over and sends over a list of questions they want you to plan in. How would you deal with this?”).

Your interviewer wants you to get into the weeds of how you’d handle this sort of logistical or real world issue; and see if you can carve out a path to a win-win outcome.

The behavioral interviews make up for half, if not more of your onsite loop. In each round, you’ll face 3-4 questions tied to the Leadership Principles with follow-ups for each. 

The questions usually start with “tell me about a time” or “give me an example of” because the rounds exist to examine your past work and understand the quality of decisions you took. 

Expect questions like:

• Give me an example of a goal you’ve had where you wish you had done better.
• Has it ever happened that you and a client had different goals for a project?
• When was the last time you got feedback from a teammate that changed how you work? 
• Tell me about a time you insisted on the highest standards.
• Tell me about a time you had to learn a new domain quickly to run a study.
• What kind of tradeoffs have you made when you’ve had to deliver directional findings fast?
• Tell me about a time you pushed for a customer need the team wanted to deprioritize.

Amazon suggests that you frame behavioral answers using the STAR framework. To give you a better edge, we recommend that you take the classic STAR framework and build it out into STAR+ (Situation, Task, Action, Result + the X-Factor: Learning) to structure your stories. The X-Factor at the end - Learning. You end each story with a personal takeaway and how it changed the way you work. This way, you’ll demonstrate intellectual humility which implicitly links to a lot of the LPs. Read more on Preparing for Amazon’s behavioral interview. 

This is an hour-long interview with a trained interviewer that’s outside your hiring team. Their role is to ensure that every new hire performs better than 50% of current employees in a similar role. 

In Memoirs of an Amazon Bar Raiser, Carlos Arguelles writes “BRs are a unique part of the Amazon culture. You lead the debrief (which includes all the interviewers in the same room debating their data points) and make the final hire/no hire decision. You have veto power over all hiring decisions (a hire cannot happen without your thumbs up.)”

Most Bar Raiser interviews are mostly behavioral and built around a deep dive/retro on one of your previous projects. They’ll ask about the extent of your contribution or ask you to defend certain decisions you made. 

Generally speaking, you should be prepared for this round to be a rigorous LP-alignment audit with some pressure-testing around your narrative. 

Read our Amazon's Bar Raiser Interview: A Comprehensive Guide to the Process for 6 tips on how to answer their questions.

Amazon grades candidates by rating specific leadership principles as either a Strength (ST), Satisfies (SA), Development Needed (DN), or No Evidence (NE). Interviewers use these ratings to then cast a final vote to hire you on a scale of Strongly Inclined > Inclined > Not Inclined > Strongly Not Inclined.

• L4: $128K 
• L5: $206K
• L6: $280K 
• L7: $496K
  

View Amazon UXR compensation data on Levels.fyi