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It\\u2019s easy to think of data scientists as \\u201cpeople who explore and model data\\u201d. Bur in reality, the job description is much more flexible: your job as a data scientist is to solve problems that people actually have with data.

You\\u2019ll notice that I wrote \\u201cproblems that people actually have\\u201d rather than \\u201cbuild models\\u201d. It\\u2019s relatively rare that the problems people have actually need to be solved using a predictive model. Instead, a good visualization or interactive chart is almost always the first step of the problem-solving process, and can often be the last as well.

And you know who understands visualization strategy really, really well? Plotly, that\\u2019s who. Plotly is a company that builds a ton of great open-source visualization, exploration and data infrastructure tools (and some proprietary commercial ones, too). Today, their tooling is being used by over 50 million people worldwide, and they\\u2019ve developed a number of tools and libraries that are now industry standard. So you can imagine how excited I was to speak with Plotly co-founder and Chief Product Officer Chris Parmer.

Chris had some great insights to share about data science and analytics tooling, including the future direction he sees the space moving in. But as his job title suggests, he\\u2019s also focused on another key characteristic that all great data scientists develop early on: product instinct (AKA: \\u201cknowing what to build next\\u201d).