For data science and AI professionals, experience with less frequently used and growing, tools, frameworks and platforms commands a generous premium.

This is the second time we've reported on O'Reilly's recent Salary Survey. Back in September, when the report by MIke Loukides was published, our coverage was about the marked gender gap in pay  - women working in Data and AI are paid on average $126,000 compared to $150,000 for men - and the finding that certification is associated with higher salaries, see Get Certified, Earn More.

This time we look at how salaries are impacted by the programming languages, 

First how do salaries vary with the industry respondents work in? The survey was of recipients of O'Reilly's Data & AI Newsletter and the analysis was of 2,778 respondents from the United States. The greatest number worked in the software industry 20% of the total followed by consulting (11%) and healthcare, banking, and education (each at 8%).For the purpose of looking at salaries the “computer industry” was divided into four segments: computer hardware, cloud services and hosting, security, and software, Average salaries in these industries ranged from $171,000 (for computer hardware) to $164,000 (for software) and were grouped together at the top of list of industries, ahead of carriers/telecommunications, retails/ecommerce and banking/finance. The industry that had the average salary ($150,000) was  advertising/pr/social media. The lowest salaries were in nonprofits/trade associations ($103,000) and education ($106.000). Salaries for technical workers in government were slightly higher ($124,000).

The O'Reilly survey found that the most popular programming languages for data and AI practitioners were Python (61%), followed by SQL (54%) and JavaScript (32%).These languages were in the middle of the salary range - Python $150,000; SQL $144,000; JavaScript $146,000 - while top of the list were Rust over $180,000 and Go  $179,000 followed by Scala ($178,000):

In the report Loukides speculates why Rust, Go and Scala commands a higher salary and suggests:

The supply of talent for newer languages like Rust and Go is relatively small. While there may not be a huge demand for data scientists who use these languages (yet), there’s clearly some demand—and with experienced Go and Rust programmers in short supply, they command a higher salary. Perhaps it is even simpler: regardless of the language someone will use at work, employers interpret knowledge of Rust and Go as a sign of competence and willingness to learn, which increases candidates’ value. A similar argument can be made for Scala, which is the native language for the widely used Spark platform.

Notice that respondents who said they didn't use any programming languages had a slightly higher than average salary.  They represented 10% of respondents and Loukides commented:

It’s possible they worked entirely in Excel, which should be considered a programming language but often isn’t. It’s also possible that they were managers or executives who no longer did any programming.

Respondents were also asked tools they used for statistics and machine learning and what platforms they used for data analytics and data management. The most common responses to the question about tools for machine learning or statistics were “I don’t use any tools” (40%) or Excel (31%). Those who didn’t use tools had an average salary of $143,000, and Excel users had an average salary of $138,000, both below average:

The popular machine learning packages PyTorch (19% of users, $166,000 average salary), TensorFlow (20%, $164,000), and scikitlearn (27%, $157,000) occupied the middle ground while it was uncommon packages that commanded the highest salaries. h H2O (3%, $183,000), KNIME (2%, $180,000), Spark NLP (5%, $179,000), and Spark MLlib (8%, $175,000). Commenting on this Loukides writes:

It appears that salaries are higher for people who work with tools that have a lot of “buzz” but aren’t yet widely used. Employers pay a premium for specialized expertise.

The survey revealed a similar scenario with regard to data frameworks. The the most common response was from people who didn’t use a framework; that group also received the lowest salaries (30% of users, $133,000 average salary). Expertise in well-known frameworks attracted above average salaries - Spark (19% of users, $172,000); Kafka (15% of users, $179,000); and Hadoop (15% of users, $166,000). However the highest salaries were reserved for platforms or frameworks with very few users. Right at the top came Clicktale (now ContentSquare), a cloud-based analytics system for researching customer experience, used by only 0.2% of respondents who attract an average salary of $225,000:

The bottom line here has to be, if you are looking for good remuneration, don't hesitate to learn about the newest and trendiest technology.

More Information

O'Reilly 2021 Data/AI Salary Survey (pdf) 

Related Articles

Get Certified, Earn More

Developer Pay According To Stack Overflow

Comments

Make a Comment or View Existing Comments Using Disqus

or email your comment to: comments@i-programmer.info