Amazon is a global leader in e-commerce, cloud computing, and artificial intelligence, well-known for its customer-centric approach and innovative solutions. As a Research Scientist at Amazon, you will engage in cutting-edge research across various domains, from machine learning and optimization to quantum computing and sustainability.

The position requires deep domain knowledge, strong technical skills, and the ability to manage and deliver high-quality research projects. You will work closely with cross-functional teams, including data scientists, engineers, and product managers, to drive impactful research that shapes the future of Amazon's services and products.

In this guide, Interview Query will walk you through the interview process, covering common interview questions and valuable tips to help you succeed. Let’s dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Amazon as a Research Scientist. Whether you were contacted by an Amazon recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV is shortlisted, a recruiter from Amazon's Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Amazon Research Scientist hiring manager may be present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Initial Technical Interview

Upon passing the recruiter screening, you’ll be invited to an initial technical interview. This stage often involves a virtual interview featuring discussions about your background and previous projects, typically lasting around 45-60 minutes. You may expect questions that probe into your research methodology, project achievements, and technical know-how in areas like machine learning, AI, and image processing.

Potential questions include discussing your work with CNN models, DSA questions, and how your research could be applied to business settings. It’s crucial to be well-prepared to discuss challenges, results, and mathematical formulations related to your work.

Onsite Interview Rounds

If you successfully navigate the initial rounds, the next stage is the onsite interview loop, which includes multiple interview sessions. These sessions aim to evaluate your expertise in core technical areas and your alignment with Amazon’s Leadership Principles.

There may be a mix of Behavioral Interviews, Technical Interviews, and Research Presentations. Typical technical rounds can involve: - Machine Learning concepts - Optimization problems - Statistics and probability - Data structures and algorithms

Behavioral questions will often focus on scenarios requiring accountability, decision-making under pressure, and customer-oriented problem-solving.

Quick Tips For Amazon Research Scientist Interviews

• Know Amazon's Leadership Principles: Leadership principles at Amazon are a crucial part of the evaluation. Prepare stories that exemplify your alignment with these values.
• Brush Up on Technical Foundations: Be sure you are solid on your technical fundamentals, especially in areas relevant to the Research Scientist role—like machine learning algorithms, coding in relevant languages (Python is a good one to know), and other domain-specific knowledge.
• Understand Practical Implications: Amazon may test how well you can translate theoretical research into practical applications. Show examples from your past work where you turned theoretical knowledge into impactful solutions.

Typically, interviews at Amazon vary by role and team, but commonly Research Scientist interviews follow a fairly standardized process across these question topics.

• Write a program to determine the term frequency (TF) values for each term in a document. Given a text document in the form of a string, write a program to determine the TF values for each term. Round the term frequency to 2 decimal points.

• Write a Python program to check if each string in a list has all the same characters. Given a list of strings, write a Python program to check whether each string has all the same characters or not. Determine the complexity of this program.

• Write a query to return all neighborhoods with 0 users. Given two tables, a users table with demographic information and a neighborhoods table, write a query that returns all neighborhoods that have 0 users.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to check if two strings are anagrams of each other. Given two strings, write a function to return True if the strings are anagrams of each other and False if they are not. Note that a word is not an anagram of itself.

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What are the benefits of dynamic pricing, and how can you estimate supply and demand in this context? Explain the advantages of dynamic pricing and describe methods to estimate supply and demand for implementing this strategy.

• Can you determine if an A/B test with unbalanced sample sizes will result in bias towards the smaller group? Analyze the results of an A/B test where one variant has 50K users and the other has 200K users. Determine if the unbalanced sample sizes will bias the test towards the smaller group.

• What is the Martingale strategy and how might it be used in online advertising? Describe the Martingale strategy and discuss its potential applications in online advertising.

• How would you find the user with the highest average number of unique item categories per order? Given two tables, user_orders and ordered_items, identify the user with the highest average number of unique item categories per order. Assume there is only one user with the highest average.

• What methods could you use to increase recall in Amazon's product search without changing the search algorithm? As a data scientist at Amazon, you want to improve the search results for product searches but cannot alter the underlying search algorithm. What methods could you employ to increase recall?

• How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician? Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician. Ensure each explanation is appropriate for their understanding level.

• What happens when you run logistic regression on perfectly linearly separable data? Given a dataset of perfectly linearly separable data, what would be the outcome when you apply logistic regression?

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. In which scenarios would you prefer a bagging algorithm over a boosting algorithm? Provide examples of the tradeoffs between the two.

• What’s the difference between Lasso and Ridge Regression? Explain the differences between Lasso and Ridge Regression.

• What is the probability that item X would be found on Amazon's website? Amazon has a warehouse system where items are located at different distribution centers. In an example city, the probabilities that item X is available at warehouse A or B are 0.6 and 0.8, respectively. Given that items are only listed on the website if they exist in the distribution centers, what is the probability that item X would be found on Amazon's website?

• What's the probability of rolling at least one 3 with 2 dice? You are playing a dice game with 2 dice. What is the probability of rolling at least one 3? Additionally, what is the probability of rolling at least one 3 given N dice?

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to someone without a technical background.

• What are time series models and why do we need them? Describe what time series models are and explain why they are necessary when simpler regression models exist.

• What statistical test would you use to determine which parcel is better for shipments? You are in charge of shipments at Amazon, with two types of parcels, A and B. Packages in parcel A are damaged with probability p, and in parcel B with probability q. What statistical test could you use to determine which parcel is better? What would the test conclude if p=0.4 and q=0.6, given data from 200 shipments, half with parcel A and half with parcel B?

What is the average salary for a Research Scientist at Amazon?

Q: What is the interview process like for a Research Scientist position at Amazon?

The interview process for a Research Scientist position at Amazon usually starts with a phone screening, followed by a series of technical and behavioral interviews. You can expect questions on leadership principles, your past research work, and technical topics such as machine learning, data structures, and domain-specific knowledge. The process might also include live coding, brainteasers, and a final onsite interview with multiple rounds.

Q: What are some common technical topics covered in the Amazon Research Scientist interviews?

Common technical topics include machine learning algorithms, optimization techniques, statistical modeling, and computer vision. Specific questions may delve into CNN architecture, matrix-related problems, and techniques for reducing overfitting. You should also be prepared to discuss your previous projects and any relevant mathematical formulas related to your domain.

Q: How important are Amazon's Leadership Principles in the interview process?

Amazon's Leadership Principles are extremely important in the interview process. A significant portion of the interviews will focus on behavioral questions aligned with these principles, such as customer obsession, bias for action, and ownership. Be ready to provide stories and examples from your past experiences that highlight these values.

Q: How long does the interview process typically take?

The interview process can be lengthy, often taking several months from the initial application to the final decision. There may be delays and multiple rounds of interviews, so patience and persistence are key. Communication from Amazon's side is sometimes slow, but you will receive feedback after each stage of the process.

Q: How can I best prepare for Amazon's Research Scientist interviews?

To prepare effectively, it is recommended to practice common interview questions and refine your technical skills. Specifically, focus on coding problems, research breadth, and in-domain knowledge related to machine learning and optimization. Using Interview Query to simulate interview scenarios and get feedback can be particularly helpful in your preparation.

The journey to securing a Research Scientist position at Amazon is as rewarding as it is challenging. Candidates can expect a comprehensive interview process that spans multiple rounds, delving into both technical expertise and behavioral competencies, particularly Amazon's Leadership Principles. Prepare for insightful discussions on your past projects, detailed technical queries on machine learning algorithms, optimization problems, and more. Feedback is generally prompt, and the interviewers supportive, contributing to an overall fair experience. To boost your chances of success, ensure you practice common interview questions and scenarios you might encounter.

If you want more insights about the company, check out our main Amazon Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineers and data analysts, where you can learn more about Amazon’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Amazon machine learning engineer interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!