10 Skills of Effective Data Scientists
The field of data science is a relatively new one, with a growing handful of academic programs making early attempts at setting a rubric. As a result, its definition and the roles it encompasses remains up for debate. There are plenty of broad definitions, but the suite of skills at the disposal of successful practitioners is more oblique. Sure, data science involves statistical modeling and computer engineering, but what precisely does that entail? A recent post at Data Science Central by Mitchell A. Sanders presents an in-depth survey of the skills shared by effective data scientists in the industry.
Sanders segments the activities of a data scientist into three discrete categories:
- Programming and Database Skills
- Business Domain Expertise and Knowledge
- Data Modeling, Warehouse, and Unstructured Data Skills
- Statistical Tool Skills
- Math skills
- Visualization Tool Skills
- Storytelling Skills
Sanders goes further in his breakdown, acknowledging the diversity of opinions in the field by citing other takes on the topic. Some of the other lists recognize personality traits that are just as important as technical skill and expertise, such as curiosity, innovative thinking, and the indefinable yet useful quality of intuition.
At Data Community DC, NASA Research Scientist Oscar Olmedo diagrams the process of data science in a pyramid which shares much with Sanders’ outline, though it differs in the segmentation of tasks:
By Paul M. Davis read more