data visualization engineer and data analyst
Predicted and analyzed Google's global ad revenue. Advised executive decision makers.
Published research and introduced new "comet chart" to reveal statistical "mix" issues in data.
Freelanced as data visualization engineer and analyst with clients including Kickstarter, Google, Yale, and Stamen.
Much of my work shows how the obvious insight from aggregated data is misleading.
Good at convincing people that data & math is fascinating, interesting, and something they can do [teaching high school math, giving presentations, and through the interactive visualizations I create]
Spent last 6 months in Alaska, Oregon, Namibia, Mozambique, Egypt, Chile, and St. Louis. Amazing adventures. Now excited to get back to work.
And, in a little more detail...
My interest in data visualization originally grew out of my work as the lead analyst for Google's global search ads revenue. As an analyst, I found visualization to be an especially powerful tool and I created custom visualizations tailored to address a particular data question or explore a particular type of data. This led me to collaborate with Google's data visualization research team led by Martin Wattenberg and Fernanda Viégas. I built an interactive data visualization tool to tackle a challenge I'd often faced as an analyst. At InfoVis 2014, I presented the resulting research, Visualizing Statistical Mix Effects and Simpson's Paradox, and introduced the "comet chart". The associated paper was published in the Proceedings of IEEE InfoVis 2014.
Some of my favorite projects are those where the "obvious" understanding of the data is misleading or masks some deeper truth. This is exemplified in my research on visualizing Simpson's paradox and in my OpenVisConf talk Everything is Seasonal. Similarly, I enjoy finding other ways to see familiar data that reveals a different perspective and interpretation. One of these projects, comparing the sizes of countries around the world, was featured on Flowing Data. Other examples include "weather circles" and same pixel/different picture.
I also enjoy creating custom visualization tools for analysts, engineers, and scientists to enable them to make new discoveries in their data. I'm most interested by identifying what characteristics of the data might be most analytically important, and finding ways to reveal those characteristics visually and meaningfully.
In fall 2014, I studied the intersection of data, computers, and art in collaboration with 14 other developers/artists at the School for Poetic Computation.
As a freelancer, I have created both exploratory and explanatory data visualizations as well as doing visualization-based data analysis, working with clients including Kickstarter, Google, Yale, and Stamen.
Most recently, I spent the last 6 months of 2016 traveling the world, and recently returned excited to get back to work. If you are interested in hiring me full-time or for freelance work, please be in touch.
Email me at email@example.com.
The popular Flowing Data blog featured my work in July 2015's post "A More Realistic Perspective of Country Sizes."
Alberto Cairo included my research on Simpson's paradox and the new comet chart on page 219 of his book The Truthful Art.
Profiles & Interviews
On July 19, 2016 Jonathan Schwabish interviewed me as episode #54 of the PolicyViz Podcast: On this week’s show, I chat with Zan Armstrong (in person, no less!) about her work analyzing and visualizing data. I first met Zan in the spring at the OpenVisConf following her great talk on seasonality. We talk about data visualization and all sorts of data-related issues in this week’s show, so take a careful listen and take a look at all the great links posted below.
In Spring 2016, I collaborated with the Stamen on 3 projects: Amazonia Under Threat, Atlas of Emotions, and visualizing metegenomics with Berkeley's Banfield Lab. Before I headed out for 6 months of travel, I sat down with Eric Rodenbeck, founder, CEO, and creative director of Stamen, for a conversation about my experience working with the team.
In Jan 2016, Ian "asked some of the most skilled practitioners I know how they went about learning d3 and an interesting pattern emerged: start (small) projects with an idea and no idea how to implement it, and then try to implement it." I was one of the four practitioners featured in the article. Read it here.