Communications of the ACM
ACM Careers
Essential Skills and Traits of Elite Data Scientists
What does it take to be data science whiz? Here are some important attributes and skills, according to IT leaders, industry analysts, data scientists, and others.
- Critical thinking. Data scientists need to be critical thinkers, to be able to apply objective analysis of facts on a given topic or problem before formulating opinions or rendering judgments.
- Coding. Top-notch data scientists know how to write code and are comfortable handling a variety of programming tasks.
- Math. Data science is probably not a good career choice for people who don't like or are not proficient at mathematics.
- Machine learning, deep learning, AI. Data scientists need to have a deep understanding of the problem to be solved, and the data itself will speak to what's needed.
- Communication. The importance of communication skills bears repeating. Being able to communicate with multiple stakeholders using data is a key attribute.
- Data architecture. It is imperative that the data scientist understand what is happening to the data from inception to model to business decision.
- Risk analysis, process improvement, systems engineering. A sharp data scientist needs to understand the concepts of analyzing business risk, making improvements in processes, and how systems engineering works.
- Problem solving and good business intuition. In general, the traits great data scientists exhibit are the same traits that are exhibited by any good problem solver.
From ITworld
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