Data scientists are the hottest new occupation in the tech industry. They command an average salary of over $115,000. But are they earning more than software engineers? Not necessarily.
Here’s what we’ll cover:
Most of this decade’s leading companies—Apple, Netflix, Uber, Airbnb—sell digital products serving millions of customers in thousands of locations. The two pillars of companies of the 21st century are software and data. Both software engineers and data scientists are enjoying increasingly high demand in the workforce.
The software powering these products needs to be functional, intuitive, and bug-free. The data that informs the experience of these products needs to be efficiently stored, analyzed, and interpreted. In 2020 and beyond, both software engineers and data scientists will play crucial roles in shaping the world.
But who earns more: software engineers or data scientists? At the outset, both these careers and their related fields are lucrative, paying above-average salaries. What's more, these career paths no longer require a bachelor's degree or master's degree. Software developer reigns at #1 in US News' 100 Best Jobs list, while data science is among the top 15 fastest-growing jobs in the United States. In essence, both are excellent options.
In this article, we’ll show you what role pays better—and why.
Studies show that the demand for software engineers is expected to increase in the coming years.
Data science is the field of collecting, storing, organizing, analyzing, and interpreting large data sets. A data scientist is one who leverages an organization’s data to help leaders make informed decisions based on data analytics and statistical analysis. Data scientists might also apply machine learning and artificial intelligence techniques, as well as data mining, to build predictive models.
Data scientists are in demand in virtually every industry, from financial services to food delivery.
Data science and software engineering are both technology jobs, but they require mostly different skills. Each role brings with it technological complexities and real-world business problems. And each of these fields uses different tools, techniques, and processes to address them. Software engineering might be more suited for someone who works well within structures and prefers having guidelines and processes to follow. Data science might be better for someone who flourishes in chaos, finding insights in unstructured data.
Both software engineering and data science involve programming to a certain extent. The primary difference between the two is the final product.
It is critical to note here that while data scientists also use software to perform their functions, they do not build these software products or data architecture; there are software engineers dedicated to building software solutions for big data called data engineers.
A highly experienced software engineer earns $178,000 on average, while a data scientist with comparable experience and skills earns $155,000. (Source: Robert Half’s Salary Guide.)
A similar difference is seen across experience and skill levels. However, any professional’s remuneration is a function of several factors. Let’s look at them one by one and understand the gaps.
Payscale shows that software engineers in the San Francisco Bay Area have a pay range of up to 40% higher than the national average, proving that Silicon Valley is still the dream destination for software engineers. This is true of data scientists as well, though the difference from the national average is slightly lower at 27%.
Seattle comes a close second for both roles, offering higher salaries than the rest of the country. With tech giants like Microsoft, Amazon, and Facebook’s engineering teams operating out of Seattle, this comes as no surprise.
Some of the best tech companies offer competitive salaries to attract skilled software engineers as well as data scientists.
Amazon and Facebook appear to pay top software engineer salaries — $150,000 on average. Uber, Bloomberg, and LinkedIn come close at $140,000.
For data scientists, Apple and Facebook once again top the list, closely followed by Uber, Microsoft, Google, and Amazon.
Both being related to technology jobs and related fields, this transition is certainly possible. If you’re a software engineer looking to transition, focus on developing skills in mathematics, statistics data wrangling, machine learning, data mining, data visualization, and other data science skills, either through self-learning or an online course or bootcamp. If you already have skills in a programming language like Python or R, widely used in data science, you’re all set.
Software engineering and data science are both highly sought-after technology jobs. Given how much of software development today involves aspects of data science, the two groups of professionals work in parallel, across similar levels of the organizational structure. More often than not, the difference in salaries for the two roles is negligible.
If you’re excited by building products and writing code, choose software engineering. If numbers and insights inspire you, choose data science. Either way or whichever job title you choose, you gain the skills necessary and negotiate confidently for a top salary.
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