National reports in the United States regularly emphasize the need for qualified engineers to enter the workforce to solve present and future challenges for society. Such advancements often encourage an understanding and application of data science, a field that combines areas like mathematics, statistics, programming, analytics, and artificial intelligence. Despite its rapid growth and increasing integration across topics and industries, data science is not often incorporated directly into engineering curricula. Understanding when and how to utilize data science methodologies can provide non-computing engineers with a competitive edge professionally, offering valuable insights, improving decision-making, and driving innovation in their respective domains. Given the benefits of learning and employing data science, we explored the views of non-computing engineers and how they may influence their attitudes and practices. We defined non-computing engineers as individuals focused on an engineering field who are not pursuing computer science or computer engineering-specific formal education or degrees. To assess varying perspectives, we conducted a study utilizing Reddit posts. Reddit is a platform where many engineering students and practitioners may talk openly about different topics. We collected data using web scraping and analyzed it using a couple of Natural Language Processing (NLP) techniques, including Latent Dirichlet Allocation (LDA). Using the top keywords, we then took a manual approach, using whole posts for context to perform thematic analysis to derive the topics. Our findings suggest that non-computing engineers are generally positive about data science and its potential applications. They see it as especially important for 1) Career Prospects and Opportunities; 2) Ongoing Professional Development and Upskilling; and 3) Practical Applications. As such, it can provide opportunities for career preparedness, fostering new competencies, and a need to gain hands-on experience using data science to create value and solve problems. The results of this work can have important implications for educators, administrators, and professionals looking to incorporate data science into engineering praxis.
