Understanding the Self-Efficacy of Data Scientists

Abstract

The self-efficacy of Brazilian data scientists' professional profiles was analyzed to launch new views on this profession, marked by fast technological changes and with a body of knowledge and an incommensurable scope of skills, as understood by these professionals. A grounded theory was built using a qualitative approach. It found the coping theory to explain the phenomenon after the emergence of self-preservation, as an adaptation strategy, and self-efficacy, as a striking feature of the profession. A practical implication is that self-efficacy has trade-offs both to threats and opportunities in the process of becoming a data scientist. The present article describes the value of the coping theory makes possible an in-depth view of the analytical expertise influence on threats and opportunities, and on technology adaptation choices.

What Can Managers Learn From Professional Poker Players About Decision-Making?

“…This is directly related to the capabilities -that is, the ability to be able -of these individuals to identify, store, process, interpret and use meaningful data to make decisions based on facts and data (Oliveira & Handfield, 2019;Sincorá et al, 2018;Talberg, 2019). This way, players with skills in using IT resources are better able to properly explore data sets, prepare data for analysis, and integrate data sets from different sources and systems (Louro et al, 2020;Schläfke et al, 2013).…”