Creating Adhoc Data Science Teams for Local Politics


It's election season, and you're on the campaign trail. You've set up your website, you've been knocking on doors, making phone calls, getting endorsements, and attending rallies, but there's only so much you can do to get your message out there. You need data to make informed decisions about where to focus your efforts, but you don't have the time or resources to hire full-time data scientists. What do you do?

In this talk, I'll discuss how to create adhoc data science teams to help with local elections. We'll cover how to structure projects to collect data, continually inform your campaign strategy, and communicate with a variety of backgrounds.

This talk will discuss how to create ad hoc data science teams to support local political initiatives. It will cover using notebooks to collect and analyze data, as well as how to effectively communicate findings to:

* candidates (or measure/bond leads)
* campaign staff
* the media

By the end of this talk, you'll have the tools you need to enable people to make data-driven decisions on the campaign trail and communicate.


Kyle is the Chief Architect at Noteable and a core developer of the IPython/Jupyter project. He wants to help build great environments for collaborative analysis, development, and production workloads for everyone; from small teams to massive scale. His passion for open source has enabled him to build better systems with staying power, enable peers, support companies he's worked for, and drive growth. As an active member of local politics, Kyle has focused on schools, active transportation, transit, and housing all to have a good impact on climate change and equity.

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