How I Became a Data Scientist as an International Student with Broken English
Took a long time but I found what I enjoy doing for the rest of my life
Currently, I am a data scientist over 4 years of experience. I want to delve into my own journey — a gradual process of discovering my passion for data science. It took me quite a while to figure out my career path, but the journey was certainly worthwhile. I hope my story serves as inspiration to anyone out there who may be struggling to become a data scientist or doubting their own abilities.
Arriving in the States with limited English Skills
“I work at a meth lab”. This was how poor my English was when I first moved to the States all by myself. I didn’t know there was a difference between “meth” and “math”. It took me about a year to finally grasp the distinction. I wasn’t involved in making drugs; instead, I was a math tutor at The Math Lab at City College of San Francisco (CCSF).
After failing the college entry exam in South Korea, I relocated myself to the United States, believing I can build a new life here. I was a bold and naive 18 years old girl. I vividly remember the first few days in downtown San Francisco, where I couldn’t even manage to order a simple cup of coffee at Starbucks. I stumbled over my words, leaving the employee perplexed, and she responded in rapid English. Feeling overwhelmed, I resorted to a bow of thanks, a gesture from Korean culture, before hastily leaving the store.
Discovering my passion for Statistics at a Community College
To improve my English skills, I enrolled in a community college. There, I explored various subjects, including German, Swimming, Computer Science, Math, English and Statistics. Amidst this exploration, I found my passion. My childhood dream was to become a math teacher, driven by my love for Mathematics and children. As I pursued relevant courses, I found that taking Statistics was a game-changer. I fell in love with every aspect of it, which ultimately led me to pursue a major in Statistics when transferring.
Becoming a First Generation College Student
My parents never left South Korea, let alone attended a college. When I gained the admission to multiple universities, they were unfamiliar with prestigious institutions like UC Berkeley. Nonetheless, they were willing to support me financially, covering tuition and living expenses, proud in the knowledge that their daughter was embarking on a college education.
Struggling to Pursue Actuarial Career
As a junior majoring Statistics at UC Berkeley, I explored potential career paths. I joined both Statistics club and Actuarial club to gain insights. Initially, becoming an actuary seemed like a logical choice — I enjoyed solving math problems, passed a few actuarial exams, and completed an actuarial internship. However, I encountered difficulties in securing a full-time actuarial position. Despite this setback, I now see it as a learning experience. Looking back, I realize that my current job brings me more satisfaction than I would have found in an actuarial role.
Introduction to Data Science in Business
Upon graduating, I had two job offers: a data analytics internship at a startup and a merchandise planner position at an e-commerce company. I chose to become a merchandise planner and had the opportunity to collaborate with data scientists there. They were working on developing a machine learning model for demand forecasting and pricing, a topic I had throughly enjoyed studying during my time at UC Berkeley. Witnessing the practical application of machine learning in business was incredibly rewarding. Seeking guidance, I turned to a data scientist I knew at the company. He advised me to pursue further education to become a data scientist, especially considering the visa challenges I faced as an international student.
The Value of a Master’s Degree in Statistics (now known as Applied Data Science)
I moved to Pittsburgh, PA to pursue my master’s degree at Carnegie Mellon University (CMU). Taking the Statistical Computing course with Professor Alex Reinhart enhanced my Python skills, while the Data Mining course from Professor Sivaraman Balakrishnan prepared me well for machine learning interviews. I went to their office hours almost every week and they were tremendously helpful. The quality education I received at CMU enabled me to leverage my coding skills, project experiences, and coursework knowledge to successfully navigate data science interviews.
Finally Landing 4 Job Offers for a Data Analyst & Data Scientist
It wasn’t easy. Over a span of 4–5 months, I applied to approximately 700 jobs, targeting junior data scientist positions. I didn’t know which company was hiring foreign employees, so I applied all. Despite the uncertainty, I received responses from over 20 companies and progressed to the final stages with 4 of them, all of which extended job offers.
The Lesson Learned
It took considerable time and effort to reach this point, and the journey was challenging and unpredictable. Job hunting was fraught with setbacks and stress, but my belief in my abilities kept me going and ultimately led me to success in this field. I firmly believe that anyone equipped with the right skills and a positive mindset can forge a career in data science. I hope my story serves as inspiration to others!
