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Find out what it means to be a data scientist at Amazon! Their salaries, roles and required experience, types of data positions, and interview process.
Amazon.com, Inc. is the largest internet company in the world, and unique in its focus on the "customers’ desire for lower prices, better selection, and convenient services." Amazon is the world's largest online retailer, and that's in addition to its products in AI Assistant technology, streaming services, and cloud computing. Founded by Jeff Bezos in his garage in 1994, Amazon now has nearly 1.3 million employees across the world, after adding around half a million in 2020 alone.
Amazon has over 200 million subscribers on its two-day delivery services, Amazon Prime, as well as over 150 million mobile users on the Amazon app, with the Amazon Marketplace moving more than $300 billion worth of products over the course of 2020. That's not to mention Amazon owning almost half of the world's public cloud infrastructure market through its subsidiary, Amazon Web Services (AWS), through which it earned over $380 billion in net sales revenues.
On top of this, all is Amazon's "customer-obsessed" business model, pushing Amazon Data Scientists to leverage its data to create the best experience for all of its users across Amazon's various platforms.
Data roles at Amazon do some of the most cutting-edge research in artificial intelligence and machine learning to create forecasts and optimize algorithms for their customers.
Here's a quick overview of the types of data positions at Amazon and their respective salaries, with a comparison to the national average.
Total compensation at Amazon also includes health & dental insurance, life insurance, 401k with company match, company RSUs, and bonuses. Check out levels.fyi for a deeper dive on Amazon salaries and benefits.
Let's take a look at additional qualifications for these roles.
Qualifications for Business Analyst
Qualifications for Data Scientist
Qualifications for Data Engineer
Teams of Data Scientists perform a vital function at Amazon, working with Amazon's broad set of products across varying teams and levels across the organization. This includes the entire e-commerce branch of Amazon, as well as other specific product and business areas. Amazon's customer-centric business model means any data role will consistently focus on providing value for the customer. At the same time, the responsibility and focus of a data position can vary depending on the team and department you are hired for.
The types of roles include:
Business & Marketing
The e-commerce branch of Amazon is the most well-known branch of the multinational technology company with millions upon millions of both sellers and buyers. There are 1.9 million active sellers on the Amazon Marketplace, with that number growing by more than a million new users every single year. As the world's largest marketplace, Amazon has data positions working on potential problems at every aspect of the business, from minimizing buyer risk to optimizing the supply chain.
A role in Business & Marketing will:
With Amazon owning almost half of the world's public cloud infrastructure market, it's only natural that there is a strong need for data positions that focus on building, maintaining, and optimizing their data practices and processes, not to mention the data infrastructure needed for the other products under the Amazon umbrella. Working cross-functionally with a variety of other teams at Amazon, these data engineering teams play a vital role in working with the absolutely enormous amount of data produced by Amazon Web Services.
A role in Data Engineering will:
That truly outrageous amount of data Amazon has access to gives it all sorts of opportunities to use data-driven insights and solutions to create value for customers from, for example, search results and video and product recommendations. Taking great strides in the realm of machine learning, these teams have an impact on millions of Amazon's users around the world.
A data role in Machine Learning will:
Now that you know more about the roles and responsibilities of Amazon data science teams, here's a brief overview of how the interview process works.
Amazon has a fairly standard (if extensive) interview process for the data scientist position, from the initial phone call screening through the hiring manager interview, and finally the full day on-site interview.
Online Application & Phone Screening
After your online application and resume are submitted, there is an initial screening phone call with a recruiter. This is a short half-hour conversation where the recruiter goes over your resume and experiences, and then briefly explains the role, team, and team's relative position within the company.
Next up for the Amazon data scientist position is the technical screen, which will go more in-depth about your data experiences and technical expertise. This will include questions about statistics, coding, algorithms, and product design, with the data science coding questions being done over a shared code editor.
Full-Day On-site Interview
After passing the technical screen, there is a full-day on-site interview. There will be around 5 interviews split throughout the day, with a lunch break in between. The interviews will have a mix of behavioral and technical questions.
Note: the interviews will be virtual and the interview format may vary for the duration of the pandemic.
Interviews for the data scientist position at Amazon always include the typical questions about your background and experiences, commonly with many variations of "Tell me about a time where…"
Product Sense & Business Cases
These questions help gauge your interest in Amazon as a company, as well as your knowledge of Amazon as a business.
Data Analysis & Coding
This portion of the interview tests your coding ability, covering technical details of the code with specific examples.
We recommend that you refer to these Amazon Data Scientist Interview Questions!
These questions cover practical applications of your coding ability and how you approach data problems. Don't forget the natural follow-up to any modeling question: "How can you tell that your model is working?"
Remember to explore Amazon's Career FAQs, and check out Amazon's own page on Interviewing at Amazon. Check out our forum of Amazon's Data Science interview questions here. We also write blog posts that walk you through how to solve specific interview questions in our Data Science Interview Questions series. Be sure to research the most recent interviews and salary information for the role on Glassdoor. Levels.fyi also has up-to-date information on salaries and benefits.
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