AMAZON Data Analyst INTERVIEW Questions

Amazon, renowned as a global e-commerce giant, stands out from traditional marketplaces due to its vast scale, featuring an extensive array of millions of products. In the United States, Amazon dominates over 50% of the online market, showcasing its substantial influence. Since its establishment in 1994, Amazon has consistently pursued its overarching objective of becoming the ultimate “one-stop-shop,” a mission facilitated significantly by its meticulous reliance on data. This data-centric approach holds significant relevance for individuals gearing up for Amazon Data Analyst interviews, highlighting the pivotal role of data in driving Amazon’s operational strategies.

Here are some of the finest Amazon Data Analyst Interview Questions.

The round details are as follows-

1.      HR Initial Screening

2.      Technical Screening: Round 1 – coding, machine learning, and algorithm

3.      Technical Screening: Round 2 – Leadership Principles

4.      Onsite: Round 1- Leadership Principles, general questions related to your experience in your previous jobs.

5.      Onsite: Round 2 – statistics

6.      Onsite: Round 3 – machine learning, SQL skills, and technical skills.

7.      Onsite: Round 4- behavioral questions, system design.

8.      Onsite: Round 5 – human relations

HR Initial Screening

• Are you open to relocation for this position?
• What factors are motivating your decision to explore new opportunities?
• How long have you been in your current role?
• Can you provide a detailed overview of your professional journey as outlined in your resume?
• What motivated you to seek employment at Amazon?
• What specific aspects of the job description caught your attention and made you interested?
• Could you share your salary expectations for this position?
• What is your earliest availability to start in this role?

The initial stage of the interview process at Amazon involves a recruiter phone screen lasting 30-60 minutes. This call serves the dual purpose of evaluating whether you meet the fundamental qualifications for the job and assessing your compatibility with Amazon’s culture. The recruiter will delve into standard questions about your background, experience, and salary expectations. Beyond these aspects, candidates often overlook the significance of this call as an opportunity for the recruiter to gauge their alignment with Amazon’s Leadership Principles.

Understanding and articulating your comprehension of these principles becomes crucial during this stage. Moreover, the phone screen provides a chance to establish rapport with the recruiter, offering insights into the role and the reasons behind its recruitment. Successfully navigating this phase involves not only meeting the basic job requirements but also showcasing cultural fit and a genuine understanding of Amazon’s guiding principles.

Technical Screening: Round 1

In this round, candidates’ technical proficiency is assessed through inquiries spanning coding, machine learning, and algorithms. Amazon data analysts pose these questions to evaluate applicants’ readiness for the role by gauging their technical capabilities in these crucial areas.

1. Calculate the cumulative cost of each customer’s purchase and output their last names, locations, and IDs in alphabetical order based on last names.
2. Formulate a query to retrieve the total sales for each product in the month of February.
3. Define convex and non-convex cost functions and elucidate the distinctions between them.
4. Provide an explanation for the concept of overfitting in the context of data analysis or machine learning.
5. Share your perspective on whether adjusting the prime membership fee would have an impact on the market. If so, elaborate on how this change might influence the market dynamics.

Technical Screening: Round 2

In the second round of the technical screening, the focus shifts to the examination of Leadership Principles. Amazon places significant emphasis on this aspect, and the questions in this round revolve around assessing candidates’ alignment with and understanding of the company’s Leadership Principles.

1. What motivated your decision to join Amazon?
2. Describe a situation where you effectively managed a disagreement with your manager.
3. Can you share an instance when you faced challenges in meeting project deadlines and how you addressed it?

Onsite: Round 1

In this stage of the interview process, the emphasis is on Amazon’s Leadership Principles, as they play a crucial role in enhancing customer satisfaction. Anticipate broad questions centered on your personal experiences and professional background during this round. Amazon’s focus on leadership principles stems from their recognition of the profound impact it has on elevating customer satisfaction levels.

1. Detail a project you managed, highlighting your approaches to ensure timely completion.
2. Discuss a challenge you encountered while working on a project and how you addressed it.
3. Can you elaborate on your key strengths and areas you are actively working on for improvement?

Onsite: Round 2

In the second round, questions will continue to center around leadership principles, but the expectations are elevated. Additionally, there will be a focus on statistical knowledge, recognizing its integral role in data analysis, and assessing your proficiency to determine your suitability for the position.

1. Provide insights into specific projects listed on your resume, discussing your roles and contributions.
2. Among Amazon’s leadership principles, which resonates with you the most? Conversely, which one do you find most challenging and why?
3. Share an experience where you devised a solution for a particularly intricate situation.
4. In scenarios where there’s a high ratio of negative to positive data, how would you effectively address the imbalance?
5. For an engineer, elucidate the significance of the p-value.
6. When faced with collinearity, what steps would you take to address the situation?

Onsite: Round 3

During the third round, expect inquiries pertaining to machine learning, SQL proficiency, and technical skills. These skills, particularly SQL and machine learning, are highly sought-after in the field of data analysis.

1. Provide an explanation of a machine learning model and elucidate its relevance in practical applications.
2. How do you communicate technical concepts such as R-square to non-technical colleagues? Share your approach.
3. Talk about a specific machine learning technique that captures your interest and explain why.
4. Contrast the characteristics of a queue and a stack.
5. In your perspective, are there any distinctions between an array and a linked list? If so, what are they?

Some more Technical Questions-

Question: Explain the purpose of a DISTINCT clause in SQL.

Answer: The DISTINCT clause is utilized to retrieve only unique (distinct) values from a query result.

Question: Compare and contrast UNION and UNION ALL in SQL.

Answer: The UNION operator extracts distinct rows from the queries specified, whereas UNION ALL retrieves all rows, including duplicates, from both queries.

Question: How do Window Functions operate in SQL?

Answer: Window Functions perform calculations at the row level with a set of related values. Unlike aggregate functions like SUM(), window functions don’t consolidate the rows into a single value; instead, they return output for each row.

Question: Differentiate between a primary key and a foreign key in a database.

Answer: A primary key is a column or set of columns in a table that uniquely identifies rows in that table. On the other hand, a foreign key is a column or set of columns in a table whose values correspond to the primary key values in another table.

Question: Explain the distinctions between the SQL functions LEAD and LAG.

Answer: LEAD provides values from rows occurring after the specified row, while LAG provides values from rows occurring before the specified row.

Onsite: Round 4

In the fourth round, anticipate behavioral inquiries alongside questions related to system design. A comprehensive grasp of the end-to-end process of creating and launching systems from inception to completion is essential for addressing these questions effectively.

1. Share an experience from your professional background where you collaborated with non-technical colleagues.
2. Describe a situation when your perspective diverged from that of your colleagues and how you navigated through it.
3. Provide an explanation of SCD (Slowly Changing Dimension).
4. Outline the design of a Data Warehouse (DWH) tailored for the media team to compile statistics about their services.

Onsite: Round 5

In this segment, the focus lies on interpersonal skills, where the evaluation centers around your behavioral aptitude. Amazon places a significant emphasis on the human relations capabilities of their data analysts, recognizing the importance of adeptly servicing individuals from diverse backgrounds and locations.

1. Describe an instance where you provided support to a team member.
2. Outline your professional aspirations for the upcoming five years.
3. What factors influenced your decision to join Amazon?
4. Do you have any specific inquiries you would like to pose to us?

The Data Monk services

We are well known for our interview books and have 70+ e-book across Amazon and The Data Monk e-shop page . Following are best-seller combo packs and services that we are providing as of now

1. YouTube channel covering all the interview-related important topics in SQL, Python, MS Excel, Machine Learning Algorithm, Statistics, and Direct Interview Questions
   Link – The Data Monk Youtube Channel
   
2. Website – ~2000 completed solved Interview questions in SQL, Python, ML, and Case Study
   Link – The Data Monk website
   
3. E-book shop – We have 70+ e-books available on our website and 3 bundles covering 2000+ solved interview questions. Do check it out
   Link – The Data E-shop Page
4. Instagram Page – It covers only Most asked Questions and concepts (100+ posts). We have 100+ most asked interview topics explained in simple terms
   Link – The Data Monk Instagram page
5. Mock Interviews/Career Guidance/Mentorship/Resume Making
   Book a slot on Top Mate

The Data Monk e-books

We know that each domain requires a different type of preparation, so we have divided our books in the same way:

1. 2200 Interview Questions to become Full Stack Analytics Professional – 2200 Most Asked Interview Questions
2.Data Scientist and Machine Learning Engineer -> 23 e-books covering all the ML Algorithms Interview Questions
3. 30 Days Analytics Course – Most Asked Interview Questions from 30 crucial topics

You can check out all the other e-books on our e-shop page – Do not miss it

For any information related to courses or e-books, please send an email to nitinkamal132@gmail.com