Dan Saber

Fear, loathing, Data Science

Where We Go From Here: Covid-19 and Politics

In my last post, I discussed how and why Covid-19 would change work. You can find it here, but TL;DR: New digital norms will form, permanently imbuing the knowledge economy with a remote-friendly flavor. It seems equally clear that Covid-19 will have... Continue Reading →

Where We Go From Here: Covid-19 and Work

Allow me to get this out of the way: I would prefer if none of this had happened. I would prefer if the novel coronavirus hadn’t jumped from its original pangolin/bat/civet host and into a human being. I would prefer... Continue Reading →

In Praise of Friction

I used to have a Spotify subscription. As a music fan, nothing could be better. Within hours of signing up, Spotify learned my musical proclivities so well that I began to hang out on the app’s Discover tab waiting for... Continue Reading →

Programming Note

Hello, loyal readers (i.e., Mom)! Recently, I’ve begun using this blog for more than just Data Science writing (e.g., writing essays, complaining about the Bay Area, etc.). That said, I know many of you are primarily interested in my technical... Continue Reading →

Destroy Your Country’s Economic Mobility with This One Neat Trick

I live in the Bay Area. The Bay Area is extremely expensive. (Source not cited.) Oppressively high housing costs have led to all kinds of fun social pathologies. San Francisco’s homelessness crisis is only the most well-documented. There is also… Continue Reading →

For The Economist: Corporate Wokeness and Campaign Finance

I was interested in whether "woke" companies donate disproportionately to Democrats, or if their embrace of progressive causes is one big branding exercise. The answer? Kinda both (but mostly branding)! I'm unbelievably proud to say that my findings were published... Continue Reading →

Partner-Driven A/B Testing at Coursera

EDIT: Thanks to commenter gruddock, I learned that the conference organizers took down the talks from YouTube. Please see here for the slides. They include complete speaker notes. I recently attended the Data Science Innovation in eLearning Conference (hosted by Udemy... Continue Reading →

Time Keeps on Slipping: Exploiting Time for Causal Inference with Difference-in-Differences and Panel Methods

Note: This post assumes a passing familiarity with linear regression. Aside from that, it's a highly applied intro to D-in-D regression and panel data techniques. In Due Time In one of my favorite episodes of Futurama, the universe experiences "time skips."... Continue Reading →

For Inside Big Data: Making the Leap from Data Science Hopeful to Practioner

I wrote a post for Inside Big Data on transitioning into Data Science -- a topic I'm actually qualified to give advice on! It’s a familiar dilemma. You’ve done your research, read some books, taken some online classes – and at long... Continue Reading →

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