Unveiling the Data Science Landscape: Insights from StackOverflow Developer Survey 2022

Introduction

In the world of data science, numbers are like storytellers. They reveal tales of trends, ambitions, and the ever-changing world of technology. As technology evolves, so do the roles of Data Scientists. In this fast-paced field, they take on diverse responsibilities.

We’re on a journey through the Stack Overflow Developer Survey 2022. Our goal is to uncover what Data Scientists do, the languages they use, how education links to salaries, which languages are most sought after, and the issue of gender-based pay gaps.

So, let’s start our adventure and find out what secrets these numbers and surveys have in store for us, even if you’re not a tech wizard!

Part 1. Data Scientists wear different hats!

What additional responsibilities do Data Scientists commonly take on in their current positions?

We start by examining the roles and responsibilities commonly taken on by Data Scientists beyond their core tasks. Are they also involved in software development, engineering, or other roles?

Data Scientists and Machine Learning specialists often wear multiple hats, with 33.49% as Developer Backends, 28.13% as Data Engineers, and 24.69% as Fullstack Developers. Additionally, 23.01% engage in Data or Business Analysis, and 18.2% work as Academic Researchers, bridging academia and practical applications in their dynamic tech roles.

Part 2. Data Scientists’ Favourite Programming Languages

Which programming languages are most frequently utilised by Data Scientists?

Next, we identify the programming languages that Data Scientists rely on in their day-to-day work. Which languages dominate their toolkit?

Python reigns as the most popular language, used by a whopping 89.09% of Data Scientists and ML Specialists. They typically use more than four programming languages on average. In addition to Python, the top five favorites in this group include SQL (57.59%), showing its importance in data work. There’s also Javascript (38.97%) and Bash shell (38.55%), essential for web development and automation. HTML/CSS (34.09%) completes the top picks, highlighting their role in the toolbox of these tech-savvy experts.

Part 3. Programming Languages That Are In Demand

Which programming languages do Data Scientist want to work with over the next year?

We examine which languages Data Scientists aspire to use in the coming year and identify any emerging trends and rising stars in the world of programming languages for the future.

Rust is on the rise! It’s now one of the top five languages that Data Scientists and Machine Learning specialists want to work with in the next year.

Python is still the leader at 76.51%, while SQL (41.69%) remains essential for data tasks. Javascript (30.36%) and Bash shell (25.66%) are valuable for web development and automation. Rust’s 25.36% popularity shows it’s gaining traction in the data and machine learning community.

Part 4. Higher Degree Means Higher Salary (or not always?)

Does holding a higher degree correlate with earning a higher salary?

We investigate whether holding a Doctorate degree influences earning potential among developers in general. Is a higher level of education correlated with higher salaries?

The correlation between education levels and salaries among different types of developers, including data scientists, is notable. Interestingly, those with Doctorate degrees lead the way with the highest median salary of $87,948, demonstrating the value of advanced education in this domain. Bachelor’s degree holders are also well-compensated, earning a median salary of $70,771, while Master’s degree holders closely follow at $70,206.

Part 5. Gender-Based Salary Disparities

Is there a gender-based salary disparity among Data Scientists, with male Data Scientists earning higher salaries than their female counterparts?

Lastly, we examine whether there’s a gender-based salary gap within the developer community, with a particular focus on Data Science roles. Do male developers earn higher salaries than their female counterparts?

Median salary of male Data Scientists is a bit higher than female Data Scientists. Median salary of male and female Data Scientists are $68,677 and $61,179.50, respectively.

Nevertheless, it’s important to acknowledge that this result could be influenced by the significantly higher number of male survey respondents compared to female respondents. Hence, it’s essential to examine the number of respondents based on gender to understand any potential biases in the result.

Is there any gender bias in the survey response?

From the above plot, we can see that the survey is overwhelmingly dominated by male respondents, and the presence of female participants is notably low, particularly in the top five countries with the highest response rates. For example, in the United States, only 6.02% of respondents are female, while Canada has 5.03%, the UK has 5.02%, India has 4.29%, and Germany has 3.51% female participants. This significant gender disparity emphasizes the importance of actively promoting diversity and inclusion in survey participation to create a more balanced and representative dataset.

Conclusion

In our exploration of the Stack Overflow Developer Survey 2022, we’ve uncovered valuable insights:

1. Data Scientists are versatile, with over 33% taking on Backend Developer roles.
2. Python’s dominance at 89.09% highlights its critical role.
3. Rust’s emergence (25.36%) signals a potential shift in programming trends.
4. Education matters, with Doctorate holders earning the most, but practical skills are significant.
5. Median salary difference exists between male and female Data Scientists.
6. Disparity may be influenced by a significantly higher number of male survey respondents.

For access to the code and further analysis, please refer to the link provided on my Github, accessible here.

Data Source

The Stack Overflow Developer Survey 2022 data for this project can be accessed here.