My First Data Science Conference
Reflecting my first major event in the industry
Hey everyone hope y’all are well. Goodness knows April was a tad hectic for me but I’m still here! April had one of the most major things happen along my journey. I volunteered and attended my first conference! Specifically the New York R Conference. It was a blast! Let me tell you how it went down.
Day 0
This was the day before the conference officially began. As a volunteer, we came in to get everything up and going so the next two days would be a smooth ride. We got tables set up, name tags ready, gift bags for our speakers, and a bit of heavy lifting. Let me tell you all that the next time you go to a technical conference of some sort, remember that a ton of planning and moving went down behind the scenes so you could just focus on learning and connecting. Also please remember to thank the volunteers if you run into them. Now, on to the fun stuff.
The Conference: Day 1 & 2
I was super excited like a kid in a candy store. I was surrounded by smart, data people. My people. Everyone all gathered to share knowledge and advance our collective understanding of tools, the R language, and data science. There was a bunch of R schawg thanks to the kind people at RStudio (the company responsible for the IDE virtually everyone there uses) Microsoft, Pearson and a few more. Of course I had to snag some stuff:
Day 1 had some really solid speakers. One most notable being the person responsible for making the lives of R users everywhere soooo much easier. The founder of RStudio JJ Allaire. He demonstrated a package that allows an R user to quite literally write a book using the programming language. He showed us R for Data Science. (Pssst it’s a free book online and will be coming out in print soon. ) Jared Lander who’s the host of the NY R meetup and one of the main people responsible for putting this conference did a talk aptly called “R for Everything”. I thought it was a joke at first until he showed us emailing, git, and even how to wipe someone’s hard drive clean from within R. Wow. By far my favorite talk from Day 1 was by Drew Conway. His talk was a reflection on the Data Science field in NYC, the not-so-straightforward career paths forward, issues in the field, and solutions. Definitely check it out.
During the intermissions I really took time out to see who I can find. I met data analysts and data scientist who worked at interesting non-profits, tech companies like Roku, stats people, and even some fine people from DataCamp! Needless to say, I fan-boyed a little. There was also a woman I met who wasn’t really technical but came to the conference to see what she can bring back to her company. She knew data science wasn’t a magic bullet but there was a lot of potential in the good it can do. The other attendees were a great reflection of data science it self: a melting pot of different fields gathered together to really draw something from data and solve problems. Kinda poetic really.
Surprisingly the founder of Pandas was there as well. For those of you who don’t know, Pandas is an Python package that makes working with data for python users much easier. As Jared quipped it “Makes Python usable” haha. The founder of Julia was there as well. I was happy to see that at a language specific conference speakers from other languages were allowed on board. This way we can all from each others difference, try something new, and push data science forward. I like this kind of cross pollination.
Day 2 was also filled with great speakers. I sadly missed Vivian Peng’s “The Feels” talk live but she was super nice to talk to me about it during one of the intermissions. For any of you who’ve made a visualization or plot watch this. In short Vivian makes the argument and shows an example of being able to invoke emotions with the visualizations we make. It’s pretty powerful. I also really enjoyed Elena Grewal’s talk about how data science is done over at AirBnB. They take a great effort in creating open knowledge for the team in the form of an internal repository, they spend money on classes, and they have take home tests as well as in person interviews. They create hybrid teams where a data scientist is at the core supporting other teams. They wrote seem pretty good articles here in their publication.
At the end of the conference I was super inspired. I was truly made aware of how broad data science as a field was. Health, non-profits, business, transportation, disaster prediction statistics etc. Almost every field imaginable can be furthered by people who can understand and analyze the data they create. They can make things cheaper, be more prepared, answer questions better and so much more. It definitely solidified for me that I want to remain in this field and touch as many different industries as possible while also making a difference. And so, I will keep learning. The only really fault I had with the conference is that I wished there was a bit more diversity in the speakers. Other than that, great job.
You can view the videos from the conference on this page. It also includes the slides of the presentations that weren’t recorded.
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