Renaissance man, (or woman) revolutionary, a profile of the skills carried by the mythical data scientist
Accenture is hiring 250 data scientists – Cognizant says they don’t exist yet – but we need 200,000 of them.
Here is a list of basic skills required to be a data scientist.
1) Functional sector specific expertise. You must know your industry in depth. For example financial services data scientists need to understand risk and compliance. Life science and biometrics need to understand exploratory thinking.
2) Technology expertise with Hadoop. Whether you yourself are an expert in hadoop or you can build a team
3) An understanding of statistics. Although a hangover from the days when business intelligence ruled it is still important.
4) A strong grounding in mathematics.
5) Visualisation – having the ability to visualise patterns and demonstrate to the business so that they can see it and appreciate it.
6) Presentation skills, stage presence. To be a successful data scientist you will spend a lot of time convincing audiences that what you find has value.
The data scientist role has been described as "part analyst, part artist." Anjul Bhambhri, vice president of big data products at IBM, says, "A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a Renaissance individual who really wants to learn and bring change to an organization."