This post was originally published on Medium You’re a data scientist, and you’ve got a predictive model — great work! Now what? In many cases, you need to hook it up to some sort of large, complex software product so that users can get access to the predictions. Think of LinkedIn’s People You May Know, which mines your professional graph for unconnected connections, or Hopper’s flight price predictions. Those started out as prototypes on someone’s laptop, and are now running at scale, with many millions of users.

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This post was originally published on Medium Yesterday was the 2016 National Day of Civic Hacking, a Code for America event that encourages people with technology and related skills to explore projects related to civil society and government. My friend Josh Tauberer wrote a thoughtful post earlier about the event called Why We Hack —on what the value of this sort of event might be — please read it. For my part, this year I worked on one of the projects he discusses, understanding the impact of DC’s rent stabilization laws and what potential policy changes might yield.

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This is an updated version of an article first published on Medium on Oct. 24, 2015. I love my smartwatch, way more than I thought I would when I bought it, over a year ago. It’s a Moto 360, which is still better looking than the Apple watch, I think. Why do I love it? It’s not the health monitoring. I turned that junk off as soon as I got the thing.

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This post was originally published on Medium Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician. — Josh Wills (@josh_wills) May 3, 2012 There are different types of data scientists, with different backgrounds and career paths. With Sean Murphy and Marck Vaisman, I wrote an article about this for O’Reilly a few years back, based on survey research we’d done.

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This post was originally published on Medium I’m the Director of Data Science at EAB, a firm that provides best-practices research and enterprise software for colleges and universities. My team is responsible for the predictive models and other advanced analytics that are part of the Student Success Collaborative product that’s used by academic advisors and other campus leadership. We’re hiring data scientists, and I wanted to publicly say a few things about the roles we have advertised.

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The below is a public version of a post originally posted on an internal blog at the Education Advisory Board (EAB), my current employer. We don’t yet have a public tech blog, but I got permission to edit and post it here, along with the referenced code.  Data Science teams get asked to do a lot of different sorts of things. Some of what the team that I’m part of builds is enterprise-scale predictive analytics, such as the Student Risk Model that’s part of the Student Success Collaborative.

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Kickstarters from established profitable companies are exactly as annoying/inauthentic as food trucks from established profitable companies. — Harlan Harris (@HarlanH) September 7, 2014 Let me unpack that a bit… Hugh and Crye t-shirt Recently, Hugh & Crye, a DC-based clothing firm for men, with a novel take on sizing, recently did a Kickstarter campaign for their new line of fitted t-shirts. What the hell? H&C has been around for about 5 years, and based on their product growth and hiring seems to be doing quite well.

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Earlier this year, I attended the INFORMS Conference on Business Analytics & Operations Research, in Boston. I was asked beforehand if I wanted to be a conference blogger, and for some reason I said I would. This meant I was able to publish posts on the conference’s WordPress web site, and was also obliged to do so! Here are the five posts that I wrote, along with an excerpt from each.

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On Monday, October 28th, 2013, I gave a 5-minute Ignite talk entitled “Why a Data Community is Like a Music Scene” at an event associated with the Strata conference. Here’s the video: And here are the acknowledgements and references for the talk: Data Community DC How Music Works, by David Byrne my slides for the Ignite talk my blog post (written first) Photos: CBGB’s exterior: NYC - East Village: CBGB & OMFUG by wallyg, on Flickr (Creative Commons) Grafitti wall: cbgb, september 2006 (#1) by joe holmes, on Flickr (Creative Commons) Joan Jett with beer: 1977 Los Angeles, CA-Joan Jett of the Runaways backstage at The Whiskey A Go Go.

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A topographic map of Washington in 1791 by Don Alexander Hawkins. I live on the top edge of the map, on one of those hills. I’m a generally happy user of DC’s Capital Bikeshare system – just renewed my annual membership today in fact. But I don’t use it as much as I’d like to, for one critical reason. I live on top of a hill. Riders are happy to take bikes from the neighborhood to their jobs downhill, but are much less likely to ride them uphill.

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