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Jake Porway is a data scientist at The New York Times and the founder of DataKind (originally known as Data Without Borders), which matches nonprofits in need of data science with freelance and pro-bono data scientists.
Here's what he had to say about how to get into data science, how to perform well, and how to avoid key mistakes in the field.Get the Right SkillsAccording to Porway, getting into the field boils down to three key things:Practical computing skillsStatistical skillsA desire to learn"You need to be able to write scripts to scrape data as well as code up the algorithmsyou come up with in your head," Porway says.
"You should know your basic stats (and more, ideally) if you're going to really be able to assess whether the models you're building or algorithms you're writing are doing what you want.
It wasn't until he landed his job at The New York Times that he got to expand into broader data science tasks, namely Project Cascade, which tracks links from the publication across social media.The most important thing to get in the field, Porway says, is to get learning.
"Download some data, pick up some R[a language and environment for statistical computing and graphics], and start playing ...
I'd say to focus on using something like R alongside a basic stats book to guide you through exploring some data.
