We’ve had the pleasure of working with Sisi since our DC DataDive early this year, where she stepped up to lead a group who quickly (and rightfully) became known as Team Awesome. Sisi’s unparalleled enthusiasm and commitment have driven the team far beyond the DataDive in their work for D.C. Action for Children, and we’re beyond inspired by what they’ve accomplished.
Tell us about your work with DataKind.
My first exposure to DataKind was through its D.C. Data Dive in March 2012. Jerzy Wieczorek, Jason Hoekstra and I worked nearly overnight to help create the final interactive map for the non-profit we were helping: D.C. Action for Children.
I loved DataKind’s mission of using data for good so much that I volunteered to be D.C. Action’s data ambassador. We’re currently less than two months away from launching an interactive tool that came straight out of the Data Dive. I’m pumped, the entire group is pumped, and we can’t wait to see what kind of impact it’ll have.
(You can see the results from Sisi and her team’s great work here!)
What inspires you to use your data skills for good in your spare time?
I make time to have a positive impact on issues that matter to me. It’s what I do during my day job. Why not do it in my spare time?
What is one of the most surprising things you’ve learned or seen in working with data?
A lot of people who are professionals now are still figuring things out. Myself included.
Of course, there are amazing data scientists who actually did get an education in statistics and computer science. But in fields like journalism, where relatively, we’re just getting into big data (along with the rest of the revolution), many are just figuring it out as they go.
There’s been amazing work published by many many media organizations, but I’m excited by how much more room there is for us to grow.
What’s the most interesting or visually striking data project you’ve seen recently?
The Guardian’s recent interactive graphic: “Gay rights in the US, state by state.”
What does someone getting started with data science need to learn?
- Data science doesn’t have to be complicated.
- If it is, wrangling complicated data can be abnormally satisfying.
- Take things on, one project at a time, and make sure you learn something new every time.
Who are your top 3 favorite people you follow on Twitter?
If I started listing one, I’d have to list three hundred, so I’m going to pass on this one.
What music is currently queued up on your computer / iPhone/ CD player or record player?
We Are Young. By Fun.