Amazon Data Scientist Salary
An in-depth exploration into Amazon data scientist salary, the impact of experience, location, and role, and drawing comparisons with other FAANG counterparts.
People have different motivations for entering data science. They can be strangely lavish, such as not having to worry about the roof over your head or what cheese you should buy and how often. Or you are, God forbid, actually interested in putting statistics and machine learning to good use.
Or you could be one of those modest people who, their whole life, simply wanted to be left alone and “help build Earth’s most customer-centric company”. You’ll then be happy to hear this exactly is Amazon’s motto. While you’re fulfilling your dream on Earth, your boss will be fulfilling his. In outer space. In a giant…rocket.
So, whatever your reason for wanting to work there, Amazon gives everything you’d expect from a FAANG company: an exhaustive (and exhausting) selection process, good salary, prestige, good salary, working with cutting-edge technology, good salary, long hours, good salary, learning from the best in your field, and a good salary.
I haven’t mentioned this so far, but being a data scientist at Amazon guarantees a good salary. How good? We’ll come to that. Let’s first see what data scientists do at Amazon.
Role and Responsibilities of a Data Scientist at Amazon
The role of data scientists at Amazon is not significantly different from that of other companies. It always comes to those seven universal data science things.
This, however, is not the end of it. It’s just a frame for specific tasks, which depend on the Amazon team you will be a part of. And speaking of teams, there are 30 of them. They range from Alexa and Amazon Devices and Amazon Entertainment to Amazon Web Services, Human Resources, and Shopping.Practically, each of these teams requires data scientists. Most of the teams are further segmented into multiple sub-teams. A lot of opportunities for data scientists!
To demonstrate how the responsibilities always stay the same but are never the same, here are several recent job ads.
The Advertising DSP, Ads Science & Analysis Team is looking for a senior data scientist. In this role, you’ll analyze advertising data to improve bidding algorithms, ad serving, validate financial models, etc.
Another example is an ad for Senior Generative AI Data Scientist at Amazon Web Services. This position is customer-oriented, helping AWS’s customers with designing their solutions that use AWS Generative AI services.
Another example of different responsibilities is this ad for a Data Scientist at Amazon Fashion. Here, you’ll use your skills to develop ML models for personalized fit and size recommendations for fashion customers.
Factors That Affect the Amazon Data Scientist Salary
The three main factors that will determine your salary as a data scientist at Amazon are:
- Your Experience
- Job Level
- Job Location
1. Your Experience
It’s obvious – the more experience you have, the more knowledge you (supposedly) have, the higher your salary. When talking about experience, I don’t mean any working experience. It won’t hurt, though; flipping burgers at Burger King or serving customers at Starbucks does show you don’t shy away from the job, so it’s a plus at Amazon.
Unfortunately, these jobs aren’t exactly known for practicing data science skills, so they don’t count in terms of data science experience.
Every data science job at Amazon (except internships/junior positions) requires experience in the data science industry that counts. The more extensive experience, the higher salary you can expect.
Years of experience are closely related to another factor affecting data science salaries at Amazon.
2. Job Level
The data scientist job level at Amazon is directly related to the years of experience. The years of experience determine job level, while job level determines the data scientist salary range.
The levels you’ll be applying for are usually:
- DS I (L4)
- DS II (L5)
- DS III (L6)
- Principal DS (L7)
L4: The data scientists at this level range from zero to two years of experience.
L5: At this level, data scientists are required to have two to five years of experience.
L6: This level means you have five to ten years of experience in the industry.
L7: Those are typically with 10+ years of experience. You probably won’t find many ads for these positions, as Amazon usually promotes from within on level L7 and higher.
3. Job Location
Data science salaries at Amazon also depend on the job location. For the most part, what influences it are the cost of living, standard of living, and demand for and supply of data scientists in a particular city, state, or country.
Amazon Data Scientist Salary
Let’s now break down the salaries into several categories.
The total median compensation for data scientists at Amazon in the US, according to levels.fyi, is $250K. This includes base salary, stock, and bonus.
With this, you won’t exactly be very average on a national level. Using the same source, the median total compensation for data scientists in the US is $160,000. Working at Amazon will get you almost $100,000 above that.
There’s almost no need to compare this to the overall US median salary. The median weekly earnings of the nation’s full-time workers are $1,100/week or $57,200 a year. Yes, you got that right; you’ll earn almost five times that at Amazon.
Here’s a more detailed breakdown of the median data scientist salary.
Entry Level Salary
Amazon's entry-level data science salary means you’re at the L4 (or DS I) salary level. In the US, your salary will, on average, be:
Base Salary: $154,954
Stock Grant: $23,885
Total compensation: $197,454
Note: Due to levels.fyi’s methodology, these amounts don’t precisely add up. But we’re dealing with median values, so it doesn’t matter much.
Salaries by Experience and Seniority Levels
I already mentioned the entry-level salary. Let’s now take a look at the more senior data scientist levels.
DS II (L5) Salary
This Amazon data science salary level includes data scientists with 2-5 years of experience. Their salary is, on average, 20% higher than the entry-level salary. Here’s the breakdown:
Base Salary: $177,360
Stock Grant: $49,420
Total compensation: $235,620
DS III (L6) Salary
This Amazon data science salary level is for data scientists with five to ten years of experience. On average, your compensation breakdown could look something like this.
Base Salary: $184,816
Stock Grant: $119,055
Total compensation: $311,371
This is an even more significant increase than on the previous level, i.e., a more than 32% increase, on average, compared to DS II.
Principal DS (L7) Salary
If you get ten or more years of experience, the median total compensation can be comfortably above half a million dollars. Here’s the breakdown:
Base Salary: $241,255
Stock Grant: $302,455
Total compensation: $608,186
Compared to DS III, this is an almost 100% increase.
Here’s the graphical overview of the salaries on all seniority levels we mentioned.
The salary increases with experience, that we know. What’s interesting to notice is that with each salary level, the relative increases in total compensation are getting bigger and bigger. So, in Amazon, more experience really does pay off.
While the base salary and bonus increase are relatively stable, the stock grant increase is much steeper and booms at the L7 level. So much so that almost 50% of the total compensation is in stock. At this level, you get paid more in stock than in base salary.
This is in line with Amazon's policy, where they use stocks and vesting schedules to motivate their good employees to stay as long as possible with the company.
Salaries by Locations
At the bottom of each data science job ad at Amazon, you’ll see a formulation along these lines:
“Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $111,600/year in our lowest geographic market up to $212,800/year in our highest geographic market.”
The Amazon data scientist salary depends on the job location, obviously. Let’s explore this a little further.
DS I (L4) Salary by Location
Here’s the graphical representation of the Amazon data scientist salary by location.
Nominally, the salary in the Greater San Diego is the highest. The San Francisco Bay Area and Northern Virginia/Washington DC are close second and third. The Greater Seattle area is the last.
Now, let’s adjust these salaries with the cost of living using this data as a source and see what happens. I simply used mean value when there are multiple areas with their own cost of living index within one metropolitan area.
Of the considered areas, it seems DS I have it the best in the Greater San Diego area. Northern Virginia/Washington DC and the Greater Boston come second and third. You see how the cost of living is playing its role: the Greater Boston area was the second last, but now it’s the third best-paying location.
The worst, by far, is in the San Francisco Bay Area; the high salary doesn’t compensate for the extremely high cost of living.
DS II (L5) Salary by Location
For the DS II level, things are nominally almost the same. The only difference is that the San Francisco Bay Area is now the best-paying, instead of the Greater San Diego. Also, the last two metropolitan areas switched places; now Greater Boston is last instead of Greater Seattle.
We get this when we adjust the salaries for the cost of living.
The adjusted compensation still shows the Greater San Diego area is still the best choice. However, compared to the DS I level, when it was the worst choice, the San Francisco Bay Area gets to the second position. It seems hard to start in this area, but it could pay off as you gain experience.
DS III (L6) Salary by Location
At the DS III level, the New York City area suddenly becomes nominally the highest paying. San Francisco Bay Area drops to second, while the Greater Boston jumps from the last to the third place.
There’s no data for the Greater San Diego, which could mean Amazon doesn’t employ the more experienced data scientists there.
Let’s see what happens when we adjust these salaries.
The New York City area stays as the best-paying. The Greater Boston and the Greater Seattle are the second and the third.
The San Francisco Bay Area again drops from the second to the last.
Principal DS (L7) Salary by Location
There’s data only for the San Francisco Bay Area and Greater Seattle. This suggests that the Principal Data Scientists are employed only by the Amazon offices in that area.
It could make sense. The Seattle office is Amazon’s headquarters. The San Francisco Bay area is the location of AWS, Amazon Digital Music, Prime Now, Audible, Alexa, Goodreads, and Twitch.
Out of these two locations, the San Francisco Bay Area pays better. Let’s see if it’ll stay the same when we adjust the salaries.
Nope, the Greater Seattle area is a better choice!
TL;DR: The Salary by Location Summary
In short, if you’re targeting L4 and L5 levels (up to five years), Greater San Diego has the best ratio of salary and the cost of living.
If you’re on the L6 level (up to ten years), your best choice is the New York City Area.
If you’re targeting getting to the top in data science at Amazon, do it in Seattle and Greater Seattle offices – you get paid the most and sit in the Amazon headquarters. The San Francisco Bay Area is an excellent second choice.
As they say on their website, the benefits can depend on location, scheduled hours of work, and how long you’ve been working at Amazon.
But generally, you’ll get these benefits at Amazon.
Amazon vs Other FAANG Companies Data Scientist Salary
The FAANG companies are somewhat of a Holy Grail for data scientists. Working for these companies has many financial and non-financial benefits.
Since I’m focusing on the financial part, let’s see how Amazon data scientist salary compares with salaries at Facebook/Meta, Apple, Netflix, and Google.
Not too well, I’m afraid.
Amazon is second from the bottom, with only Apple paying less.
As we saw, you’ll hardly be hungry with an Amazon data scientist's salary; you’ll be paid much more than the average US data scientist and worker.
However, that salary pales compared to data scientists at Facebook/Meta and especially (wow!) Netflix. Truth be told, Amazon is very close to the third-placed salary at Google.
In conclusion, you can make bank at Amazon! As a mere beginner, you could be paid almost $200K. With years of experience, you could reach more than $600K at L7 and even more at the higher levels. (Jeff Bezos is the only one at L12, so don’t pretend to that level.)
I hear the corks popping already! But don’t get drunk on that wine yet! In the immortal words of Tyrion Lannister, the Technical Advisor to the Amazon CEO: “It's not easy being drunk all the time. If it were easy, everyone would do it. The same as being a data scientist at Goog…sorry, Amazon!”
Getting into Amazon means you must get through a rigorous selection process, and your data science skills must be top-of-the-line. StrataScratch can help you with these skills. We have in-depth guides for data scientists with 1-2 years of experience.
Wisely using such resources will put you in a better position for any data science interview, including at Amazon.