Three Lessons from Data Science
With a double major in Economics and Mathematics, transitioning into the field of data science seemed like a natural progression for me. However, it was not that simple as I initially envisioned. Wrapping my head around for loops, if statements and the intricacies of coding often left me mesmerized and sometimes demoralized, asking myself, “What the hell have I gotten into this time?” But this was just in my head. The truth is, while it felt like I was fighting a losing battle, lo and behold, my confidence was growing with each passing day. These are the three main lessons from Data Science, which I believe made the difference for me.
Get Comfortable being Uncomfortable
This is a famous statement among motivational speakers, but I experienced this firsthand. While attending a Data Analytics Boot Camp, my team members leaned towards a project on the 2020 US Elections. Admittedly, as the only international student in the group, this topic didn’t tickle my fancy one bit. Politics is boring to me; plus, I knew very little about American voting patterns or this country’s political history. Nevertheless, I was determined to give my best effort. The experience taught me that it is alright to be vulnerable and not have all the answers. So for those five weeks before our project deadline, I dug deep, asked a plethora of questions and studied US politics as if I was running for 2024. In the end, I was pleasantly surprised to see how much I absorbed on this seemingly uninteresting topic.
Fight the Imposter Syndrome
For some strange reason, I believe that perfectionism and imposter syndrome are closely related. There was a time I was just headhunting certification after certification, telling myself, “I am not ready yet for the job I want.” And this trend continued for months, until one day, I just had to suffocate my incessant need for perfection and convince myself that I was enough in that moment. Looking at any job posting, especially in data science, is indeed a very daunting experience. The list of qualifications required for these positions often serves as a deterrent to make any potential applicant quit before trying. However, your confidence should never capitulate under these circumstances, as your unique set of gifts and talents are mutually exclusive to everybody else’s. The great Danish-Icelandic artist, Olafur Eliasson, also had to overcome his imposter syndrome. When he first arrived to work as an artist in Germany after the Berlin Wall came down, he regaled that competing with other artists in this new environment was useless. He couldn’t come near to the fine works that they produced.
Nevertheless, he refused to compete at their level and decided to become the artist he was born to be. In other words, turning inward allowed him to maximize his special skill set to concoct mind-blowing works of art. Today, some of his most remarkable feats include the Harpa Concert Hall in Reykjavik, the New York City Waterfalls and the rainbow panorama atop the Aros Kunstmuseum in Denmark.
Trust the Process
To all my budding data scientists out there, this new and exciting field of work is characterized by hyper-learning. There will never be a day when you can sit back, relax and sip iced tea, boasting to yourself that you know it all. Guess what? You will constantly be learning, relearning and in some cases, unlearning. In this case, adopting an attitude of “Rome wasn’t built in a day” will help remove the burden of becoming an expert in all things data science. Like one of my mentors once advised, “Just try to learn one thing at a time.” It is incredibly frustrating to undertake the arduous task of mastering Python, R, SQL, HTML, CSS, JS, PySpark, Octave, Azure and Tableau all at once. Instead, remain committed to learning every day and you will grow from strength to strength.
