Data Scientist vs Software Engineer Salary | Towards Data Science

IntroductionSoftware EngineerData ScientistSummaryReferences
Introduction
Software Engineer
Data Scientist
Summary
References
The goal of this article is to show the differences and similarities between two popular tech roles. This information can be helpful for determining which role you would like to pursue. It can also be interesting to clear up some assumptions between these positions in regards to salary. We will deep dive into the average salary in US dollars by city and skills as well.
Disclaimer:
Like I have said for the previous articles in this series, this article aims not to compare roles as if one deserves more money or not, but is instead a guide allowing professionals in these two fields to assess against their current or expected salary. Keep in mind that these salary values are more general and no one website can be enough to assess your worth. It is the direction of these values that can be utilized as a tool for you to have when dealing with salary in the future.
The role of a software engineer can mean many different things. Some software engineers are strictly back-end, front-end, full-stack, or even machine learning engineers. With that being said, the salary can also be fluctuating quite a bit as well based on a variety of factors.
Note: this salary information has been last updated on December 15th, 2021
Here are some of the various seniority levels of software engineers and their respective salaries [3] (rounded):
Average Overall Software Engineer → $88k
Average Entry-Level Software Engineer → $77k (≤ 1 year)
Average Early-Career Software Engineer → $86k (1–4 years)
Average Mid-Career Software Engineer → $97k (5–9 years)
Average Late-Career Software Engineer → $108k (10–19 years)
Do I agree with these numbers?
No.
I think they are too low, especially the entry-level salary. However, there are certain cities that might have much higher salaries.
With that being said, here are some popular cities and some other cities with their respective salary averages for early-career software engineers (avg is 86k):
New York, New York → $107,845
Seattle, Washington → $109,061
Austin, Texas → $89,398
Atlanta, Georgia → $84,004
As you can see (and would expect), there is a considerable jump when you update to a specific city. Now, let’s add the most popular skill that can contribute to the highest salary for that city.
Below is a breakdown of those same cities from above with certain skills:
New York, New York → $135,197 with Apache Hadoop
Seattle, Washington → $127,424 with Objective-C
Austin, Texas → $121,500 with Microservices
Atlanta, Georgia → $109,927 with Cloud Computing
The takeaway here is that when you add skills that are not necessarily directly software engineering-focused, you can expect to make more money, according to PayScale.
In my personal experience, data scientist salaries can have a pretty big range (we will outline the specifics of the range below). It can depend on a variety of factors, of course, like the number of years of experience you have, the city you live in, or the specific skillset you can employ. With that being said, let’s look into some of these variations of qualifications/characteristics to see how the salary average updates.
Note: this salary information has been last updated on December 14th, 2021
Here are some of the various seniority levels of data scientists and their respective salaries [5] (rounded) :
Average Overall Data Scientist → $97k
Average Entry-Level Data Scientist → $85k (≤ 1 year)
Average Early-Career Data Scientist → $96k (1–4 years)
Average Mid-Career Data Scientist → $110k (5–9 years)
Average Late-Career Data Scientist → $122k (10–19 years)
This salary data is gathered from PayScale, and if you would like a more specific estimate, then you can use the salary survey [6].
Do I agree with these numbers?
Mostly yes.
I believe the numbers should be higher, but again, these are averages, so there can be smaller cities or more rural areas that are not as expensive and those can compose more of the estimates than the cities that cost more.
With that being said, here are some popular cities and some other cities with their respective salary averages for early-career data scientists (avg is 96k):
New York, New York → $107,092
Seattle, Washington → $111,882
Dallas, Texas → $92,724
Atlanta, Georgia → $92,758
Now, let’s add the most popular skill that can contribute to the highest salary for that city.
Below, is a breakdown of those same cities from above with certain skills:
New York, New York → $117,186 with Apache Hive
Seattle, Washington → $120,533 with Amazon Web Services (AWS)
Dallas, Texas → $112,500 with Algorithm Development
Atlanta, Georgia → $99,750 with Apache Hadoop
To me, the biggest surprise is the Dallas, Texas breakdown of adding the algorithm development skill, from ~92k to ~112k. This jump is pretty big for adding one skill. I am also not sure exactly what this skill means — which, brings me to an important point —
be sure to look into all the skills you know, and include them on your resume, because they may provide to be the biggest factor in determining your salary
As expected, cities and skills can affect the reported salary for both software engineers and data scientists. However, there were certain skills that contributed to a surprising jump in salary, and those were just the specific cities and skills we looked at. There could be other combinations as well that can be discovered when playing around with this PayScale tool.
Here is a salary summary of software engineers and data scientists:
* Average Overall Software Engineer → $88k* Average Overall Data Scientist → $97k* Data scientists may have a higher overall salary, but we saw that for the cities we investigated, their opportunity to increase salary by adding specific skills actually lead to a smaller average early-career salary than software engineers* Several factors contribute to salary, the most important most likely being seniority, city, and skills
I hope you found my article both interesting and useful. Please feel free to comment down below if you agree or disagree with these salary comparisons. Why or why not? What other factors do you think are important to point out in regards to salary? These can certainly be clarified even further, but I hope I was able to shed some light on the differences between software engineers and data scientist salaries.
Lastly, I can ask the same question again, how do you see salaries being impacted by remote positions, especially when the city is such a big factor in determining salary?
I am not affiliated with any of these companies.
Please feel free to check out my profile, Matt Przybyla, and other articles, as well as subscribe to receive email notifications for my blogs by following the link below, or by clicking on the subscribe icon on the top of the screen by the follow icon, and reach out to me on LinkedIn if you have any questions or comments.
Subscribe link: https://datascience2.medium.com/subscribe
Referral link: https://datascience2.medium.com/membership
(I will receive a commission if you sign up for a membership on Medium)
Keep in mind that for this article, the numbers are not my salaries, and are reported by PayScale instead, and other actual data scientists and software engineers. So, this article is in turn, a discussion around real data and is intended for you to better gain an understanding of what makes a role (in general), increase or decrease in salary amount based on certain factors.
[1] Photo by NeONBRAND on Unsplash, (2017)
[2] Photo by Alexandru Acea on Unsplash, (2018)
[3] PayScale, Inc., Average Software Engineer Salary PayScale, (Dec 15th, 2021)
[4] Photo by Campaign Creators on Unsplash, (2018)
[5] PayScale, Inc., Average Data Scientist Salary PayScale, (Dec 14th, 2021)
[6] PayScale, Inc., PayScale Salary Survey, (2021)