Data Science Knowledge and Skills That Reliability Engineers Need: A Survey

SUMMARY & CONCLUSIONSThis paper describes the results of a survey that was conducted to determine the knowledge and skills that reliability engineering practitioners utilize in their everyday work. The survey consisted of twenty-two (22) questions and was conducted in person at two (2) events. The first event was the 13th Annual Training Summit event held by the Society of Reliability Engineers (SRE) – Huntsville Chapter, in Huntsville, Alabama on November 29-30, 2021. The second event was the 68th Annual RAMS in Tucson, Arizona on January 24-27, 2022. In all, there were fifty (50) respondents to the survey with two being determined ineligible for lack of working in a reliability engineering role. Results showed that the vast majority of reliability engineers who participated in the survey were interested in having better data science skills for themselves and were also interested in having a teammate with data science skills. Approximately 56% of practitioners that were surveyed showed preference for having a reliability engineer with data science skills on their team. By contrast, 26% preferred a data scientist with reliability engineering knowledge and 14% had no preference. Survey results also showed that the data science skills used most frequently by reliability engineers are statistical summaries and analysis, data modeling, predictive modeling, data visualization, data cleansing/preparation, and data mining. Finally, survey results showed not only an interest hiring reliability engineers with data science skills, but also a significant openness to hiring data scientists with reliability engineering skills.