Amazon applied scientist interview questions [Updated for 2024]

Interviews for Top Jobs at Amazon

Solutions Architect Interview:

1. Tell me about a time when you took on something significant outside your area of responsibility and why was that important?
2. Describe a time you didn’t think you were going to meet a commitment you promised? How did you identify the risk and communicate it to the stakeholder/team/customer?
3. Give me an example of a time you were able to deliver an important project under a tight deadline? Did you have to make any sacrifices to meet this deadline?
4. Tell me about a time where you did not effectively manage your project and something did not get completed on time?
5. Tell me about a time when you not only met a goal but considerably exceeded expectations? How were you able to do this?
6. What brings you to be talking with us?
7. Can you describe a difficult interaction you’ve had with a customer? How did you deal with it? Thinking back, what would you do differently?
8. Can you provide an example of when you when you asked a customer for feedback? How did you use that feedback to drive innovation or improvement?
9. Sometimes customers make unreasonable requests, can you tell me about a time you pushed back or said no to a customer? What did you do in response to that request?
10. Can you give me an example of a calculated risk you have taken where speed was critical? What was the situation and how did you handle it?
11. Can you tell me about a time when you made an important business decision without consulting your manager? What was the situation and how did it turn out?
12. Do you feel you have a good understanding of what this role is all about?
13. What is your technical background?
14. Describe a software architecture you have helped design?
15. Can you think of a time you made a bad professional decision? What was the impact of the decision? What did you learn?
16. Can you think of a time when you had to make a decision but you didn’t have enough data to be sure you were making the right decision? What did you do and how did it work out?
17. Pretend that I am a CIO of a company, how would you describe the value proposition of AWS?
18. As you look back on your career so far, what would you say you’re most proud of?
19. Building trust with teams can be difficult to achieve sometimes. Can you give me an example of how you effectively built trusting working relationships with others?
20. What’s the coolest thing that you’ve learned on your own that you’ve then been able to apply in your job and to further perform your job?
21. Can you describe a time you needed the cooperation of a peer that was resistant? What was the situation and how did you handle that?

Warehouse Associate Interview:

1. Why Amazon?
2. Tell me about a time when you had to leave a task unfinished?
3. Tell me about a time when you gave a simple solution to a complex problem?
4. Tell me about a time when you invented something?
5. Tell me about a time when you had to work with incomplete data or information?
6. Tell me about a time when you influenced a change by only asking questions?
7. Tell me about a time when you solved a problem through just superior knowledge or observation?
8. Tell me about your proudest professional achievement?
9. Tell me about a time when you took a calculated risk?
10. Tell me about a time when you had to work with limited time or resources?
11. Give me two examples of when you did more than what was required in any job experience?
12. Tell me about an unpopular decision of yours?

How to Prepare for your Applied Scientist Interview at Amazon

Amazon Applied Scientist interview virtual onsite (5 rounds):

Round1: machine learning fundamentals with a senior Applied Scientist

1. Resume deep dive, project and papers, ML concepts and theories
2. Behavior question: How to handle tasks that you are not responsible for?
3. Coding: an easy level tree traversal question.

Round 2: Machine Learning with a Senior Development Engineer

1. Past experience and machine learning concepts;
2. Behavioral questions: describe the most challenging project you ever launched. How would you have done differently?
3. Coding: implementing the k-means algorithm.

Round 3: Behavioral/ Culture fit with Bar Raiser

• Why Amazon?
• How do you handle conflict with your coworker?
• How do you manage a deadline?
• A ton of follow-up questions.

Round 4: Coding and B.Q. with a software development manager

• Coding: How to determine if a string is a valid parenthesis, followed up question: what if the symbol is not a parenthesis but anything with an opening and closing symbol.
• B.Q.: tell me about a time you helped with a project you were not responsible for. There are too many tasks in your hands, and you can’t finish all of them. How do you prioritize?

Round 5: machine learning system design + B.Q. with the hiring manager

• Design product recommendation system on amazon.
• Tell me about a research paper that you recently enjoyed.
• Why amazon?
• How do you handle the pressure?

Coding questions (37%)

Amazon data scientists must write code and develop sophisticated algorithms that synthesize data coming in from multiple sources. You’ll need to demonstrate that you have the technical knowledge necessary to analyze and manipulate that data.

Expect interviewers to test you on SQL, data structures, algorithms, and some modeling. Most candidates report solving data structure and algorithm questions using Python and solving modeling questions with Python or R.

In most cases you will be coding on a whiteboard (or the virtual equivalent), but some candidates have reported entirely verbal onsite interview rounds. This shows how important communication skills are to Amazon, so practice both writing your scripts on paper and speaking through your reasoning.

Practice using the example questions below.

Amazon data scientist interview questions: coding

SQL

• Write a SQL code to explain month to month user retention rate.
• Describe different JOINs in SQL.
• What is the most advanced query you’ve ever written?
• Given a table with three columns, (id, category, value) and each id has 3 or less categories (price, size, color); how can you find those ids for which the value of two or more categories matches one another?
• I have table 1, with 1million records, with ID, AGE (column names) , Table 2 with 100 records with ID and Salary, and the following script. How many records would be returned?SELECT A.ID,A.AGE,B.SALARY FROM TABLE 1 ALEFT JOINTABLE 2 BON A.ID = B.ID+WHERE B.SALARY > 50000
• Given a csv file with ID and Quantity columns, 50million records, and the size of the data is 2gig, write a program to aggregate the QUANTITY column.

Data structure and algorithms

• Write a python code for recognizing if entries to a list have the same characters or not. Then what is the computational complexity of it?
• You have an array of integers and you want to find a certain element; what effective algorithm would you use and what is the efficiency of it?
• For a long sorted list and a short (4 element) sorted list, what algorithm would you use to search the long list for the 4 elements?
• Given an unfair coin with the probability of heads not equal to .5, what algorithm could you use to create a list of random 1s and 0s?
• Given a bar plot, imagine you are pouring water from the top. How do you qualify how much water can be kept in the bar chart? (solution)
• Write a Python function that displays the first n Fibonacci numbers. (solution)
• Suppose you have a list of strings, each of which is an English sentence. # Output a dictionary out_dict that maps a key n to the list of words that occur in n different sentences. # E.g. # Input: str_list = [ “The cat ate the fish”, “The cat saw the roses”, “The roses are red” ]
• If given an integer n and an array of numbers, give out the histogram divided into n bins.

Modeling

• How would you improve a classification model that suffers from low precision?
• We have two models, one with 85% accuracy, one 82%. Which one do you pick? (solution)
• When you have time series data by month, and it has large data records, how will you find significant differences between this month and previous month?
• How do you inspect missing data and when are they important?
• Assume you have a file containing data in the form of data = [{“one”:a1, “two”:b1,…},{“one”:a2, “two”:b2,…},{“one”:a3, “two”:b3,…},…] How could you split this data into 30% test and 70% train data?

Google prep is very different than FB prep. I believe FB prep has a template and any deviations from that template implies direct rejection. So it is very important to know the FB template and then prepare, if not your hard work will be wasted. Google questions on the other hand are very ambiguous and open ended. Google definitely follows no template. Eventually hardwork alone is not enough for FAANG and you do need luck. I suppose I will know my Google outcome in the next 7–10 days given the general slow way their process runs.

This is very disappointing to see a company like FB behave like this and expect the candidate to re-apply within one year when you are not giving any feedback for rejection in the first place. I have had rejections before also where a recruiter would atleast call and speak for 5 mins to go through the feedback. I have reached out to the recruiter for feedback but I am not sure he will respond. I have seen similar behavior by recruiter for another FB E5 post here, but did not expect this would happen to me.

I finished 350 questions on LC over 9 months. (overall LC count — 633–100 hard + 533 (medium + simple)). I did very exhaustive ML prep and finished the Grokking System Design course for System design for FB. Overall, I prepared very intensely for 3 months maxing out most of my day including squeezing time at work to prepare. I am disappointed with the FB outcome given my prep and recruiter response, but there are much more worse things happening in the world now. Wish everyone chasing FAANG and other top companies all the best!

Overall interview experience: Google interview was a bit less organized than the FB interview. However, 4 out of 6 interviewers I met this time at Google virtually were really nice to talk to. I had mostly grumpy interviewers during my first onsite 3 years back so this was a welcome change. Recruiter also seems to be a very nice person. I have to see how she handles communicating the result etc.

Interview experience: Overall interview was well conducted and interviewers were polite. I felt I did well in general except for the minor messup in coding round 2 for second question. I have seen folks mention that behavioral and ML design are key for E5 in ML which did go well for me, so I was positive.

What’s your least favourite part about being an Applied Scientist?

I’m still learning about how to manage this, but sometimes, I spend more time than I would like writing documents and in meetings. Nonetheless, it’s essential for socialising ideas and getting buy-in and feedback. I just wish I was more effective and faster at it.

Occasionally, stakeholders suggest solutions that are far more complex than it needs to be. I blame the overhyping of technology and machine learning in the media. When this happens, our team patiently tries to understand their perspective and educate them. Nonetheless, it takes considerable time and effort and distracts us from work that helps customers.

Lastly, because my work revolves around data, I’m also constrained by access to high-quality data. Delays happen now and then. Sometimes, it’s a minor lack of permissions which takes a few hours to a few days to resolve. Other times, we find that our system isn’t tracking a specific field and we need to update our trackers and wait a few months, or backfill the data.

FAQ

How is applied scientist role at Amazon?

What are the questions asked in interview of scientist?

• What has been / was your most important scientific finding? …
• Are your methods generally accepted? …
• How do your results compare with others in the area? …
• How accurate is your data? …
• How sure are you of your conclusions and interpretation? …
• Is there controversy in this area?

What interview questions does Amazon ask?

• Share about a time when you had a conflict with someone at work. …
• Tell me about a time you used innovation to solve a problem.
• Tell me about a time when you took a calculated risk. …
• Tell me about a time you had to handle a crisis.
• Tell me about a time when a team member wasn’t pulling their weight.

Is cracking Amazon interview easy?