Software developers play an increasingly important role in the success of modern businesses and it's also a profession that can afford a pretty comfortable living. According to a new report by technology training company O'Reilly, the average salary for data and AI practitioners in June 2021 was $146,000.
However, there are significant disparities and inequalities in the compensation received by developers, the survey found, which also highlighted the challenges developers have faced with career progression over the past year.
O'Reilly surveyed 3,136 respondents from the UK and US to understand the state of compensation, career opportunities and challenges in the data and AI industries.
Most salaries were between $100,000 and $150,000 yearly (34%), it found. The next most common salary tier was from $150,000 to $200,000 (26%).
Looking at salary by programming language, professionals who use Rust received the highest average pay -- over $180,000 -- followed by Go ($179,000), and Scala ($178,000).
While Python was most dominantly put to work among survey respondents, professionals who reported using this language earned around $150,000.
Explaining the differences in pay, the report's author, Mike Loukides, said proficient Rust developers were harder to come by, making them more valuable to organizations. "There's a huge demand for Python programmers, but there's also a huge supply," Loukides told ZDNet.
"There are boot camps turning out Python programmers by the thousands; it's become the standard language for introductory CS in college; and it's one of two languages that are typically used for data analysis in the sciences. For Rust and Go, the demand is smaller, but the supply is much smaller."
He added: "Rust and Go are leading-edge languages with a lot of buzz around them. If you're claiming Rust and Go competence, you're showing that you've gone beyond the basics, whether or not they're actually required for the job."
When comparing salary by tool and platform, the highest salaries were associated with H2O ($183,000), KNIME ($180,000), Spark NLP ($179,000), and Spark MLlib ($175,000). This was followed by PyTorch ($166,000), TensorFlow ($164,000), and scikit- learn ($157,000).
O'Reilly's survey also uncovered more problematic aspects of the technology jobs marketplace, including large disparities in the earning potential between men and women.
Women's salaries were sharply lower than men's, it found, averaging $126,000 annually, or 84% of the average salary for men ($150,000). This is despite the fact that women were more likely than men to have advanced degrees, particularly PhDs: the average salary for a woman with a doctorate or master's degree was 82% of the salary for a man with an equivalent degree.
The disparity wasn't quite as high for people with bachelor's degrees or who were still students, but it was still significant: these women earned 86% or 87% of the average salary for men.
"The saddest thing about that data is that it isn't a surprise," said Loukides.
It's doubly problematic said Loukides because many of the leaders of data science -- Hilary Mason, Monica Rogati, Cathy O'Neil, to name just a few -- have been women. "So, while the salary data didn't surprise me, I've always been taken aback by the claims that data science is male-dominated. But those two inevitably go together," he said.
Location was also a factor in differences in salary. Perhaps unsurprisingly, it found that salaries for developers were highest in California where the average salary was $176,000, but some respondents reported making up to $300,00 per year. This rate was followed by eastern seaboard states like New York and Massachusetts, where salaries in the neighborhood of $150,000 were reported.
Career progression was identified as a key challenge faced by the developers surveyed by O'Reilly, with many reporting that they had pursued training or professional development in the past year in the hope of soliciting a pay rise or promotion.
Nearly two-thirds (64%) of respondents said they'd taken part in training or obtained new certifications in the past months, the survey found. The top certification was for AWS Certified Solutions Architect-Associate, followed by Microsoft AZ-900: Microsoft Azure Fundamentals, and Certified Information Systems Security Professional (CISSP) certification.
Despite this, salaries for data and AI professionals were found to have only risen by an average of 2.25% per year over the past three years. Eighteen percent of respondents reported no salary increase, while 8% of those surveyed reported that their salary had actually gone down.
Offering training and development opportunities could prove crucial to retaining talent and filling digital skills gaps in teams following an uptick in tech rollouts and remote working, said O'Reilly president, Laura Baldwin.
"Given the shortage of qualified employees in fields like data science, machine learning, and AI, companies that are serious about building out their workforces must invest in learning and training to grow this talent internally," said Baldwin.
"With such a wealth of knowledgeable talent and a recovering global economy hungry to fill tech roles in digital work environments, there's never been a better time to invest in employee learning and reskilling."
Even with developers eager to progress and yet unable to secure more pay, O'Reilly's research didn't find evidence of a looming "great resignation". Less than a quarter (22%) of survey respondents said they planned to change jobs, which the report noted was generally what was expected, particularly as respondents reported being concerned about job security.
"Job turnover through the pandemic was roughly what we'd expect (perhaps slightly below normal)," wrote Loukides.
"Respondents did appear to be concerned about job security, though they didn't want to admit it explicitly. But with the exception of the least- and most-highly compensated respondents, the intent to change jobs because of salary was surprisingly consistent and nothing to be alarmed at."