Tasks

WE ALSO ASKED FOR INFORMATION ABOUT WORK TASKS: this is meant to dig a little deeper than what we can glean from a job title. Respondents could say they had “major” or “minor” involvement in each task. For the most part, tasks that correlate positively with salary also correlate positively with years of experience (and often are clearly associated with being a manager).

Among the most common tasks were “basic exploratory data analysis,” “data cleaning,” “creating visualizations,” and “conducting data analysis to answer research questions,” each with 85%–93% of the sample as a major or minor task. Data cleaning has the unfavorable distinction of being the only task for which each level of involvement means less pay: those with major involvement earn less than those with minor involvement, who in turn earn less than those who never clean data. However, this may have more to do with the fact that more-experienced data professionals (who we know earn more) tend to do less data cleaning.

Tasks that correlate most strongly with high salaries are those that involve management and business decisions, such as “communicating findings to business decision-makers,” “identifying business problems to be solved with analytics,” “organizing and guiding team projects,” and “communicating with people outside of your company”. The median salaries of respondents who reported major involvement in these tasks were €54K, €56K, €66K, and €55K, respectively.

Aside from management and business strategy, several technical tasks stood out for above-average salaries: “developing prototype models” (major involvement: €52K), “setting up/maintaining data platforms” (€50K), and “developing products that depend on real-time analytics” (€62K). For each of these tasks, respondents who reported major involvement earned more than those who reported minor involvement, and those who reported minor involvement earned more than those who did not engage in these tasks at all.