Introduction to Amazon Data Scientist Interview Process
Amazon Data Scientist Interview Process. Amazon is the largest online retailer and one of the world’s major internet companies. With so many products and services, Amazon is always looking for enthusiastic and creative data scientists to satisfy its ever-increasing data requirements.
Amazon takes pride in being known for using technology innovation to disrupt well-established businesses. Its goal is to become the most customer-focused company on the planet.
You might also know that Amazon is a conglomerate of multiple businesses, from e-commerce (Amazon.com), consumer technology (Alexa), cloud computing (AWS), streaming (Prime and Twitch), and many more. There is a vast variety of different kinds of jobs related to data science.
Here are some examples.
Search: Create and implement an Amazon.com product search ranking and recommendation system.
AWS: Assist AWS customers, such as enterprise clients, as an external consultant, or improve the technical and user experience of the AWS interface.
Alexa: Support Amazon’s key consumer-based AI product, Alexa, with information retrieval, search, and Q&A systems.
Supply Chain (SCOT): Automate and optimize Amazon’s physical commodity supply chain using quantitative analysis and modeling.
Amazon GO: It’s related to Amazon’s Go stores to improve the shopping experience of consumers.
Prime Video: A streaming service by Amazon which has different types of content that leads to customer onboarding.
Fashion Technology: Use computer vision and machine learning to deliver individualized consumer experiences for fashion shoppers.
Amazon Finance: A cross-functional team that provides support to Amazon’s numerous finance teams. The team’s primary focus is financial modeling and analytics.
Security: Build fraud and spam detection technologies to detect and deter people who are misbehaving.
As you know, these are the key areas where Amazon is providing various job responsibilities related to data science, and for the best of your interest, we have prepared a guide for the Amazon Data Scientist interview processes which will lead you to get a strong hand in these.
Amazon Data Scientist Roles
There is one thing you should know: despite the distinction in each role, the data fundamentals required are the same. The candidate should have a strong hand in machine learning, coding, statistics, and probability, and among all leadership quality is a must.
In Amazon data scientists interview the primarily responsible for providing analytics solutions, developing models, and conducting A/B testing. The fundamental focus of any data science function will differ depending on the business, team, and project.
For example, a data scientist on Alexa may work on developing customer success measures. Another data scientist on the shopping experience team might focus on running experiments to improve the user’s purchasing experience. Finally, an AWS data scientist might work as a consultant, developing custom model solutions for AWS enterprise clients.
Here are the key responsibilities and qualifications for Amazon Data Scientist :
Machine learning, statistical modeling, probability, and other quantitative techniques are used to create models.
To improve the user experience, create, conduct, and evaluate an AB test.
Measure user behaviors like onboarding, engagement, and churn with design metrics.
Create dashboards for corporate stakeholders that include crucial KPIs.
Ability to decipher complex business problems and data sets.
Using the most up-to-date modeling approaches.
SQL skills as well as computer languages like Python and R.
By using fresh data signals and modeling tools, they evaluate models and improve baseline solutions.
To turn a nebulous problem into a precise goal, collaborate with researchers, software engineers, and business stakeholders.
To both technical and non-technical partners, communicate effectively on paper and in person.
Qualifications for Amazon Data Scientist Interview
Basic qualifications for Amazon Data Scientist Interview:
2-4 years of experience with a data scripting language ( SQL, Python, R, Etc.) or statistical/mathematical software (SAS, or Matlab).
Minimum 2 years of experience as a data scientist.
Preferred qualifications for Amazon Data Scientist Interview:
Master’s degree or PhD in CS, statistics. information systems, economics, mathematics, or equivalent.
Proficiency in SQL and coding languages (R, Python, etc.)
2+ years of industry experience creating machine learning solutions for optimization, forecasting, and/or fraud detection using large-scale, complicated datasets.
2+ years of experience in data analytics responsibilities requiring data extraction, analysis, and communication in the industry.
Strong statistical modeling skills, including linear and logistic regression models.
When dealing with technical and non-technical stakeholders, you must have strong verbal and written abilities.
Experience with supervised and unsupervised clustering models.
Extensive experience in analyzing A/B tests.
Demonstrated ability to determine project goals and direction in the face of ambiguity.
The Amazon Data Scientist Interview Process
There are 3 stages of the Amazon Data Scientist Interview Process:
- Stage- 1: Recruiter’s Call
- Stage- 2: Phone Screening
- Stage- 3: On-Site Round
Stage 1: Recruiter’s Call (30-Minutes)
The first stage of the Amazon Data Scientist interview is a 30-minute recruiter screening aimed at assessing the candidate’s role-fit, culture-fit, and logistics.
Prior to the call for the Amazon Data Scientist interview :
In the applicant tracking system (ATS), the recruiter sees your job application, which includes a resume and optional cover letter. Your application is ranked algorithmically depending on how closely your qualifications match the job descriptions. Recruiters will usually contact applicants with the highest ranking first.
During the call for Amazon Data Scientist interview :
The recruiter will structure the meeting in the following manner during the call, which will last roughly 20 to 30 minutes:
Introduction: The recruiter will go through the role expectations and team in further depth.
Background information for candidates: This is your chance to tell us about yourself. “Tell me about yourself,” the recruiter will inquire. You can give a high-level overview of your academic and professional backgrounds. “Why do you want to work at Amazon?” is one of the follow-up inquiries.
The recruiter will normally inquire about the following: What city are you in? What are your technical interview availability?
Follow-Ups – The recruiter will outline the following steps, including when you should expect to hear back and how to prepare for technical rounds. This is your opportunity to ask as many questions as possible in order to plan out the technical interviews from beginning to conclusion. The more information you have, the better prepared you will be for interviews.
After the call Amazon Data Scientist interview :
Following the call, the recruiter will contact the hiring manager with remarks on the candidate’s background, technical screening, logistics, and cultural fit. The recruiter and hiring manager will move you to the first technical round if they believe you have promise.
Stage- 2: Phone Screening (45-60 Minutes)
The technical phone screen for Amazon Data Scientist interview is used to determine a candidate’s communication skills as well as technical aptitude in coding, SQL, statistics, and/or machine learning. The technical screening for Amazon Data Scientist interview takes 45 to 60 minutes and is conducted by a hiring manager or a senior data scientist, just like at other tech organizations. The interview questions change depending on the role, level, and team. In general, expect inquiries about past project experience, coding, SQL, statistics, machine learning, and/or Amazon’s leadership values.
For example, a phone screen for Amazon Data Scientist interview might look like this:
First 5 minutes- Introduction
20 Minutes- Python Coding
15 Minutes- ML breath question or a case problem
Last 5 minutes- Q and A with the interviewer
In Amazon Data Scientist interview leadership principles are often asked by the recruiters.
Stage- 3: On-Site Round (4-5 Hours)
Amazon Data Scientist interview, On-site round is the most difficult part of the procedure. You’ll be doing back-to-back 45- to 60-minute interviews with a little break in between. Overall, the interviews cover a wide range of topics, including statistics, SQL, coding, machine learning, and leadership principles.
The capacity to maintain concentration and remain calm under pressure is necessary to succeed in the on-site stage.
Let’s take a look at the rounds from the Amazon Data Scientist interview on-site stage. The rounds and questions differ depending on the function (data scientist vs MLE vs applied scientist vs research scientist).
Machine Learning: Questions on machine learning, deep learning, and case studies. The questions could be domain-specific depending on the responsibilities. For example, the MLE – Search or Applied Scientist: Search might be used to test knowledge of NLP and how to rank theories and case issues (e.g., how would you address a cold start problem?).
Statistics: Extensive coverage of statistical theory, probability, regression modeling, and experimentation, as well as case-based problems. The principles of statistics should be studied by data scientists. Expect breath-style questions like “What is the p-value?” and case-style inquiries about Amazon’s product design experimentation.
Coding: Algorithm and data structure issues are common in MLE jobs. You can expect simple algorithm inquiries that need text and/or integer manipulations from data scientists. Expect data manipulation problems that require you to manipulate a table using either vanilla code or a third-party library. Given that you are using a programming language of your choosing, such as Python or R, these inquiry types are analogous to SQL table manipulation.
SQL: The SQL round is common and expected in all FAANG interviews. In essence, you’ll be given a collection of tables and one to three problems to answer using SQL clauses like JOINS, WHERE, and GROUP BY, as well as window functions like AVG and SUM.
How to Prepare for Amazon Data Scientist interview
Now that you are familiar with the Amazon Data Scientist interview. Let’s look at the ways to prepare for it.
Do you have knowledge about Amazon’s culture?
Your work environment plays a crucial role in the quality of work and your mental health. Because Amazon is so prestigious, it’s easy to assume that you should apply without thinking things through. However, it’s crucial to realize that a job’s prestige will not make you happy in your day-to-day work. It depends on the type of work you do and the people you work with.
Talk to anyone you know who works at Amazon or used to work there as a data scientist or in another job to get a sense of the culture. The leadership concepts we covered earlier can help you anticipate what to expect, but nothing beats speaking with an insider.
Here is a recommendation for you: Inside Amazon
Learn and practice window functions as well as related functions (aggregates, ranks, and statistics creation). In the coding rounds, these are frequently requested questions.
Combining many tables and seeing the outputs can help you practice joins and the various types of joins (left, right, inner, outer). In SQL coding interviews, joins are always required.
Finally, understand how to manipulate date and time ranges and handle time series data, as they can be explicitly requested in inquiries about orders and shipment.
In addition to these technical features, you should review the principles of data structures, algorithms, and statistics. These will help you with the interview’s theory sections.
Finally, behavioral questions need you to respond honestly and directly to the point; as a result, double-check your CV and make sure you understand everything on it.
Amazon is one of the world’s largest corporations, operating in a variety of businesses and domains. Working for such a large corporation offers its own set of rewards and requirements. As a result, the amount of preparation necessary is related to the quality of Amazon’s technology. This Amazon Data Scientist interview guide will help you in conquering every roadblock come in your way.
Because the organization places a strong emphasis on coding and algorithms, it is a good idea to properly practice SQL and related subjects. Our platform also has a number of coding and non-coding questions from prior Amazon interviews that you may use to help you prepare for the interviews.
Communication skills are also important for landing your dream job at Amazon, as there are many behavioral questions posed during the interviews.
Frequently Asked Questions
HirePro is a recruitment platform. HirePro is used for virtual screening of the candidates by providing various kinds of tasks. By which you can get a score or result for your assessment via your email.
Amazon Data Scientist interview procedure might be difficult. The good thing is that it is quite constant. Because we know the framework of the interview ahead of time, it makes preparation much easier and reduces surprises.
Aspirants who want to be Data Scientist at Amazon can click here to get the full blog on Amazon Data Scientist Interview Process.
The on-site interview is divided into five rounds, each lasting one hour. You will begin with five minutes of introductions, followed by 50 minutes of interview time, followed by five minutes for any questions you may have for your interviewer.
Amazon is the second-largest company with the most number of data workers. Amazon has more than 18 thousand data workers. Land your dream job with this Amazon Data Scientist Interview Process.
Amazon assigns the following years of experience to each level:
- Experience Level 4: 1-3 Years
- Level 5: Three to ten years of experience.
- Level 6: 8-10 years of experience is required.
- Level 7: 10 or more years of experience Even at this level, Amazon likes to promote from within and seldom hires outside talent.
By far the majority of your information is collected and stored by Google. This is hardly unexpected given that their business strategy is based on having as much data as possible (and making it super easy for you to access).
Every data scientist works with various kinds of data or product enhancements. It depends on the need of the hour that is crucial for product development. An Amazon data scientist may work on Alexa, AWS, Cloud computing, etc. Here this blog of Amazon Data scientist interview will guide you through the process of hiring Data Scientist at Amazon.
First, you have to gain essential knowledge and the desired experience for about 10+ years. Then you can become a senior data scientist. This blog on Amazon Data Scientist Interview Process will help you land your dream job.