Data Science Salary Breakdown 2022

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This article is intended for those who are curious about salary breakdowns in data science for the year 2022. This information can be useful to make decisions in your career, whether it be for your current position or when interviewing for a new one. As you may know, data can vary, and therefore reporting varies as well. With that being said, we can look at three popular sites that report data science salaries to gain a better understanding of expectations. Keep reading if you want to know the ins and outs of data science salaries for this year.

Average (with some popular companies)

Photo by Julien Moreau on Unsplash [2].

You can slice a salary in most ways that you can slice any data, by a min, max, std, average, median, etc. For this section, we will look at the average values in US dollars. Keep in mind that salaries can be a combination of several things like base pay, bonuses, stock options, etc.

Glassdoor Averages:

The salaries are reported here . Disclaimer: this was last reported on December 13th, 2021, which is the most up-to-date for this site. It is not quite the year 2022, but it can still be indicative of the following year.

ZipRecruiter Averages:

The salaries are reported here . This data was updated as of June 7th, 2022, so we can put a little bit more weight on these numbers.

Payscale Averages:

The salaries are reported here [5]. This data was updated as of May 17th, 2022, so we can put a little bit more weight on these numbers when compared to Glassdoor.

As you can see, there is some expected variation in these averages across different sites. The one that is the most different — or the lowest is Payscale, while Glassdoor and ZipRecruiter are the most similar. Keep in mind that there are countless factors that can contribute to an average salary report, whether than be the number of reported salaries, or the accuracy of the site in general for other various reasons, to missing data. Now that we understand the average data science salary better, let’s look at a city breakdown.

City Breakdown

Photo by NASA on Unsplash [6].

We can use the same references for the following reported data below. City breakdown meaning has changed a lot recently with world events and work-from-home or remote-mote almost becoming the norm. Does city-specific salary matter? Will salaries normalize as people move and exchange to different cities and more rural areas? Regardless, some people and companies will still be city-centric and even if working remotely, you might be able to still justify the salary there if it has a higher cost of living, etc.

Glassdoor Averages:

I will be looking at random cities that can show a wide variety of salaries, some big, some smaller, with different costs of living, amongst other differences.

Note: I was surprised how similar these very different cities are and perhaps there is some homogenization between cities already. I was also somewhat surprised to see Seattle have the highest average by far, which does make sense in general because of the number of big companies, but was expecting to see New York be the highest in this sample.

ZipRecruiter Averages:

In this report, we will look at the top five highest average salaries.

California unsurprisingly dominates the top five, while the Seattle area sneaks in. Surprisingly, New York is missing from here — and it is not reported in the top 10 either.

Payscale Averages:

I will be looking at a few random cities here.

Everything in this specific report looks as expected with variation between more expensive cities and somewhat cheaper cities.

Seniority Breakdown

Photo by Markus Spiske on Unsplash [7].

Seniority can be defined as years of experience, or the job title, for example, 0–1 years experience, or junior data scientist.

Glassdoor Averages:

There is a big jump from the first bucket to the next, which can be important in switching jobs or continuing at a current job as your first year is completed.

ZipRecruiter Averages:

The following breakdown is unique, which I found pretty interesting. It is describing salaries from data science roles and data science-related roles that are higher in position, and perhaps the peak of seniority for certain companies.

These are all very high as expected. The first and third roles are not directly data science, but they are still interesting and could be useful to know. It is also interesting how ‘Head’ and ‘Director’ have a large difference in salary, even though they could be considered the same position.

Payscale Averages:

In this breakdown, we will look at more categorical classifications of seniority in regard to data science salaries:

Overall, these seem a little low, which does beg the question: how will inflation affect data science salaries, and by how much?

Talking about salaries can be taboo, but it does feel like that is shifting with more companies being more transparent upfront. There are countless facets that can affect salary like city, seniority, specific skillsets, negotiation skills, inflation, remote work, etc. With that being said, it is useful to look at a variety of reports on salary to gain the best sense of data science salary.

To summarize, here were the three breakdowns we dicussed:

* Average (with some popular companies)* City Breakdown* Seniority Breakdownbetween Glassdoor vs ZipRecruiter vs PayScale

I hope you found my article both interesting and useful. Please feel free to comment down below if you agree or disagree with these particular reports. Why or why not? What other factors and websites do you think are important to point out in regards to data science salary information? These can certainly be clarified even further, but I hope I was able to shed some light on the data science salary.

We are affiliated only with ZipRecruiter

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