We constantly work to give fans a personalized experience on game day and beyond; so, how do we do that? Well a big part is through data science, but how and what does that look like? Emily, one of our experienced data scientists, walks you through what her workday looks like at FanThreeSixty.
"Above all else, show the data."
- Edward Tufte
Morning — Podcasts, Coffee and Planning
I like to start every morning with a podcast episode or two while I’m driving into work. My usual rotation includes Sports Wars to hear about the great sports rivalries or the classic NPR. Once I get to work and grab a cup of coffee, I spend time catching up on Slack messages, reading the latest tech and sports news, and planning out my work for the day.
Product Meeting
On to my meetings! Twice a week I meet with the rest of the team that oversees our Mobile and Wi-Fi products. We give updates on current projects and how that relates back to our goals for the current planning period. Software engineers, project and technical managers, designers, and data scientists all work together on our products, so this is a meeting where I might get an update on the latest code release or give feedback on the data we should be collecting. This is one of the most important meetings throughout my week because it’s where I learn about new insights and performance metrics that help inform which predictive models we should focus on next.
"Data scientists create predictive models, but we also spend a great deal of time answering questions and getting to know the data."
Focus
Scattered throughout the day I focus on the core work of a data scientist. I spend much of my time querying our database, writing code, or creating visualizations to support my work. I typically get work assignments from a product manager or a director, but I’m also free to explore the data. So if I find something I want to try or am curious about, such as how a fan's mobile behavior changes when their favorite team wins, I have the opportunity to dive into the data and answer that question.
I also spend time brainstorming ideas, writing user stories, and testing different theories around fan behaviors in order to improve our products based on a fan’s habits and motivators. Data scientists create predictive models, but we also spend a great deal of time answering questions and getting to know the data.
Lunch
When I joined FanThreeSixty, one of the most surprising things to see was a huge lunch table full of people every day around noon. It’s one of the many things I love about the culture: If you’re free for lunch and want some company, you’re always welcome at the table.
Data Science Team Meeting
I’m lucky enough to be part of a team of talented data scientists who are constantly teaching me new techniques, new technologies, and who are pushing me to be better in order to support the different teams I am on. The balance of being part of both a product team and data science team means our clients are getting the best of both worlds as well: high-quality data science with the business knowledge to back it up.
Cross Collaboration
Whether it’s in a formal meeting or a casual chat, I constantly have the opportunity to work with associates from other teams. In a typical day or week I might meet with a designer for their opinion on a visualization or a client success lead to find out what clients need most from their data. FanThreeSixty has an incredibly open environment where it’s easy to ask anyone, anywhere for help because we truly do win as a team.
Summary
Data science is a great mix of individual, head-down, focused work and collaborative, engaging conversations. I am constantly learning something new both from others and from data itself, which is key in giving our clients the right tools to connect with their fans on game day and beyond.
