Why Now, Why This, Why Flatiron
If you had asked anyone in any part of the world and of any age and background what they thought would happen in 2020, I would bet you’d be hard-pressed to find anyone who saw it happening the way that it did. In many ways, it will be remembered as a nightmare of a year full of anxiety and heartache, but for me, it will also be remembered as the year we all got a reality check. Prior to this year, the idea of a global pandemic was something most people had only read about. Many of us learned the hard way how fragile life is and how much we take for granted. We overestimated how much time we really have to do the things we want to do, spend time with the people who matter to us most, and become the people we actually want to be. For my part, I learned that every day that I am not living or supporting the life I want to live is a day lost to the ether. I now know this means that many things need to change, from how I care for myself to how much time I dedicate to the ones I love. None, however, needed to be addressed more than my life’s work and the effect I want to have on others through it.
My mother would say I was the type of kid who was shy around new people, but with any kind of opening, would take the opportunity to ask anything and everything I could think of. Often to her dismay as I was rarely tactful in my curiosity. In college, I discovered sociology, and it felt like kismet. It was a path that would allow me to explore why people did what they did through methods that felt tangible and logical. Whether I studied society and families, women, deviancy, or criminology, I was always enthralled. So much that I had trouble choosing a direction when it came time to choose a career. I found myself watching old episodes of TGIF television shows in order to distract myself, and that’s when it hit me: media. I realized that just as much as any school I went to, the town I lived in, or the friends I had, the set of shows I watched, and the music I listened to were a landmark of each period. And what better way to learn about the motivations of others than through the landmarks of their lives? Little did I know how quickly I would find myself limited by the typical tools of the trade.
I was fortunate enough in my brief career as a media analyst to have the opportunity to work for two very distinct organizations. One was a nonprofit trade association, where I never had to concern myself with whether my research was sellable as much as whether it was well-founded and broadly useful; a luxury in an industry where most researchers work at networks where they focus exclusively on data that can sell ad space. My next big role was for a large but independent ad agency where I supported the national video team. Here, I had many resources, tons of creative freedom, visibility of my work vertically, all the agency perks (it will still be years before I need to buy a notebook of any size), and access to some of the most intelligent and accomplished people in the business. However, I also had no path to advancement, a boss who was as busy as she was brilliant, and no way to learn from my peers due to being the sole researcher for my department. During this job, due to the amount of flux in workload, I sometimes had time to take on personal development projects, so I was first able to try my hand at coding thanks to a continuing education program my company provided. It was here where I first glimpsed what I was missing.
I liken my first steps into the world of data science to a kid making their first visit to the circus. I thought I knew what I was in for, but the big tent holds many wondrous and sometimes frightening secrets. Pandas and pythons and seaborn! Oh my! Here I found a connection to the same goals that I had spent my life pursuing: the desire to know, understand, and continually dive deeper into all sorts of things. I learned in general terms so many of the ways data scientists were learning about human behavior, market trends, climate change, the life stages of stars, video games, and many other things. Equally amazing as what you can do with programming is the code itself: a litany of languages all used in various ways to achieve distinct but tangental goals. Languages that when understood and used correctly can seem as fluid and poetic as any of the works of Shakespeare. Couple this with a long-time love of puzzles and challenging pursuits, and it seemed all but inevitable that I would eventually go down this path. I look forward to the days I will get to spend hours writing and rewriting code, cleaning and organizing data, and eventually using that data to learn things I would never otherwise have the opportunity to learn in industries I would likely never encounter had I chosen to stay in the media space. So now I knew the way, but almost as quickly as I had decided to walk it, I came to an impasse. I had many questions, and working on my own was not going to cut it.
For me, help would come in the form of choosing to attend the Flatiron Schools Immersive Data Science Bootcamp. Help which I must acknowledge comes from the position of privilege I hold as someone who has the means and the time to pursue an alternative to self-directed learning. The program is expensive and requires 15 weeks of full-time study, during which working even part-time would be very difficult. That said, for me, having instructors and peers to work with has made a dramatic difference in my level of understanding, even in the early stage I am currently in.
There are many options when it comes to data science boot camps, so my choice came down to anecdotes from alumni, the great reviews, and the high rate of post-graduate success finding a job. (See the bottom of this post for other links I found helpful.) There also seems to be a level of prestige associated with the name, which I have already found to be helpful in some of my networking efforts. I have many thoughts now that I have entered the program, and it is a little too early for a full review, but I will say that I have been pleasantly surprised, especially with regards to my peers and instructors, all of whom are even more lovely and intelligent than I anticipated.
2020 will be unforgettable for many reasons. I, for one, will choose to look at it as eye-opening as I do my best to take away as many lessons as I can from what was, to put it mildly, a very difficult year. I also choose to look at it as the year I gained focus and finally found a way to pursue my own passion for exploration. While I don’t know what the future holds specifically, I know in my case it means many new lessons. Lessons that will come first as a data science student and, with any luck, later as a professional who is able to explore anything and everything from a unique perspective and an arsenal of programming skills at my side
While writing this blog I found these links helpful:
Without theory, data science is just about cat memes
Why I’m Leaving Data: The pros and cons of working as a data analyst
