The popular audio streaming service Spotify is known for the way it helps users seamlessly listen to the music and podcasts they love, and discover their future favorites.
ϳԹ alumnus Mike Bowen is part the company’s Experience Mission, with the goal of “enriching life with music and audio.” He currently works as Principal Quantitative User Researcher for Spotify out of Kent, Ohio.
Bowen, who graduated in 2003 with a degree in business and marketing, reconnected with ϳԹ recently, specifically the College of Communication and Information’s School of Emerging Media and Technology, to share his knowledge about data and analysis — how Spotify uses it and how students can prepare for their future careers.
This fall, Bowen partnered with Assistant Professor David Silva’s Data and Emerging Media and Technology class. Looking ahead, he is working with the School to build a potential pipeline of ϳԹ interns at Spotify beginning this summer.
We caught up with Bowen to discuss data at Spotify, careers and his work with ϳԹ students. The conversation has been lightly edited.
Tell us more about Spotify’s Experience Mission to ‘enrich life with music and audio’ and how you’re a part of it.
In practice, the “Experience Mission” is comprised of engineers, designers, product owners and researchers who look after the Spotify core mobile experience and partner platform experiences.
At a high level, I use data to help guide and inspire product strategy broadly, as well as inform tactical feature implementation. In practice, I get to analyze lots of different types of data, from our first-party log data, to surveys and more.
What inspired you to share your experience with ϳԹ students?
I felt that through my experience I might have something useful to offer to students from my undergraduate alma mater who were thinking about data and analysis as a potential career path. The School of Emerging Media and Technology struck me as a very future oriented program that I wanted to be involved with.
I also love the academic environment. The intersection of people who are in search of deeper truths, educating the next generation of thinkers and doers, and people just generally in pursuit of knowledge is really inspiring.
Spotify is known for using data to improve the platform and predict tastes in music. What are some things you’ve been able to share with Professor Silva’s Data class?
I have been in class a few times now. During my first presentation, I shared an overview of how we think about data and analysis at Spotify, the different roles that researchers have in the organization and how broad the discipline actually is. I also shared a case study of some work I had done recently that helped guide decision making through data.
My second presentation was structured more like a workshop in which we started with a very ambiguous business question (which are very common in the professional world) and started to define it in a way that we can use data to actually address it and provide a useful answer. I wrapped up by taking students through a methodology and some potential datasets that we can analyze to provide some recommendations back to the business itself.
Now that you’ve worked with these students, what types of jobs do you think they’ll be prepared for?
Jobs in data and analysis are becoming increasingly in demand, and the Emerging Media and Technology program is laying the foundation for students to become what I call “full stack” quantitative researchers.
This means understanding the role of technology in people’s lives from a human perspective, as well as going deep into the technical aspects of data, from writing dynamic code to wrangle messy data, to statistical modeling, to elegant data visualization and data storytelling to build empathy.
This summer, you’ll have your first ϳԹ intern for Spotify. What do you hope to see?
My hope is that the internship will not be “task-oriented” at all. I want to work with the intern to identify a single significant question or challenge the business is facing, then spend the summer addressing it in a rigorous way with data and analysis that, by the end of the summer, can be shared with leadership. This means defining the problem space, designing a methodology, collecting and cleaning data, robust analysis and storytelling. I want the intern to own the workstream from end to end, while I mentor and guide them throughout the process.