Hello, World! From Musician to Data Science
“Hello, World!”
It’s the first program you’ll learn to run in just about any coding language. It was initially referenced by Brian Kernighan in his book, A Tutorial Introduction to the Programming Language B. It’s also a symbolic statement — you’re stepping into a previously unknown world, so you might as well be polite and say hello to it before you start poking and prodding at the structure of it and squashing bugs along the way. Poor bugs.
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Since 2012, I’ve considered myself a professional freelance musician. Here’s an intentionally overwhelming word cloud of all the things I’ve done with a Bachelors and Masters degree in bassoon performance:
Now, I’m saying “Hello, World” to Python, my first coding language that I’m formally learning (if you disregard the html I learned so I could change the background color on my Neopets shop). On top of Python, I’m also saying “Hello, World” to the vast, ever-growing world of data science.
The reason I started down the path to music — legitimately, my dad can confirm this — was that I saw the cantina band playing in Star Wars Episode IV: A New Hope, and asked my dad, “What is that instrument?” One of the aliens was playing a bassoon, so he replied, “It’s a bassoon.” And that was it, I was head-over-heels in love with the bassoon and wanted to be a cool space musician, getting paid in space dollars that I could, in turn, spend on space beer.
As I reflect on my years as a full-time musician, I feel I’ve achieved all the things I wanted. I’ve played with the Chicago Symphony Orchestra, for sold out crowds, on television, and I’ve had my music banned from Tik Tok! My 10-year old self was interested in playing bassoon and working hard to achieve my goal of playing on another planet; my 30-year old self — after being hit with multiple recessions, an increasing wealth gap, and a pandemic — has a rekindled flame. This time, it’s not dreams of intergalactic music-making fueling the fire, it’s…
Understanding data.
What interests me most about data is effectively communicating the conclusions to others. To me, this means presenting data in a way that the audience will receive it well. Or, even better, the audience getting to see and play with the data and drawing their own conclusions. So, my blogs will eventually be full of interactive dashboards that let people play with data as if it were an analog synth; except, instead of sweet, chart-topping basslines, this dashboard pumps out sweet, data-driven conclusions.
Getting to this point in my career with music has required diligence, precision, resilience, and hours upon hours of time (and honestly a staggering amount of money), but it has also required creativity, patience, empathy, and communication. That music-career word cloud posted above doesn’t come close to the things that are possible in data science—’tis but a quaint solar system within an expansive galaxy—so it’s hard for me to explain to people what I will eventually do as a data scientist. My hope is for the skills I’ve honed through music to fuel my little ship as I blast off into the galaxy of data science.
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