Data scientists mostly just do arithmetic and that’s a good thing

Data scientists mostly just do arithmetic and that’s a good thing

Are you also wondering how you can get started as data scientist, and become a valuable team player. Understand what really matters as data scientist, and things to focus in the initial stages.

Hi, I’m Noah. I work at Basecamp. Sometimes I’m called a “data scientist.” Mostly, I just do arithmetic, and I’m ok with that.

Here’s a few of the things I worked on in the last couple of weeks, each of them in response to a real problem facing the business:

In the last two weeks, the most “sophisticated” math I’ve done has been a few power analyses and significance tests. Mostly what I’ve done is write SQL queries to get data, performed basic arithmetic on that data (computing differences, percentiles, etc.), graphed the results, and wrote paragraphs of explanation or recommendation.

I haven’t coded up any algorithms, built any recommendation engines, deployed a deep learning system, or built a neural net.

Why not? Because Basecamp doesn’t need those things right now.

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The dirty little secret of the ongoing “data science” boom is that most of what people talk about as being data science isn’t what businesses actually need. Businesses need accurate and actionable information to help them make decisions about how they spend their time and resources.

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