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data scientist


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.

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