3 skills of data scientists

Do you have a need for a Data Scientist in your organisation? If not, it might be time to start planning for one, as I’m sure your competitors or the next startup in your area will shortly utilise one.

A very interesting articles on O’Reily’s Radar – 3 Skills a data scientist needs.
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The first skill, as you might expect, is a base in statistics, algorithms, machine learning, and mathematics. "You need to have a solid grounding in those principles to actually extract signals from this data and build things with it," Skomoroch said.

Second, a good data scientist is handy with a collection of open-source tools — Hadoop, Java, Python, among others. Knowing when to use those tools, and how to code, are prerequisites.

The third set of skills focus on making products real and making data available to users. "That might mean data visualization, building web prototypes, using external APIs, and integrating with other services," Skomoroch said. In other words, this one’s a combination of coding skills, an ability to see where data can add value, and collaborating with teams to make these products a reality.

These are skills we have developed at Toast Technology and we know how to use them. These skills take time to learn and also go against the current notions of best practices where individuals will specialise in one vertical area. Now there is the need to have composite skills horizontally spanning vertical skills sets, to be able to make sense in a cost effective and reasonable time frame.

Gone are the days, of specifying everything to the nth degree. That just gets in the way of achieving a tangible outcome – the working artifacts are the coded algorithms, utilising APIs, with working code sensing the value in the data and presenting it in a meaningful way.

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