One of the first members of MOTI’s Data Equity team reflects on his journey into data science and the City of San José, and how it was supported by organizations like Correlation One that work to create equal access to the pipeline for data-driven jobs.
By: Casey Kongpanickul
For the last few years the field of data science has been one of the most desirable career paths to pursue, but how are people breaking into the field? While completing a Master of Science in Data Science from the University of California, Riverside and a data science program from Correlation One, I realized that I, like many others, come from a background that is not strictly data science. My data science journey may not be the most traditional one, but it is a path that’s becoming more accessible, so I want to share my story with others who may be asking how they can make the transition.
In 2012, I completed a Bachelor of Science in Mechanical Engineering from California State University, Sacramento. I wouldn’t classify myself as a good student and in my undergrad days, my grades definitely reflected this sentiment. In hindsight, there were many reasons I didn’t excel academically: I didn’t have any passion for the field; I did not have the support that I needed; and I lacked the self motivation to try harder. I didn’t have a lot of guidance with my first college experiences and more or less floated my way through the program without really thinking about what I wanted to do for work after graduating. This resulted in a long process to getting my mechanical engineering degree and a general distaste for academia.
I spent several years working for Intel and more generally in the semiconductor industry. During this time, I made great connections to grow my network, as well as developed skills as an IC (integrated circuit) package designer. Essentially, I was designing the interfacing component (substrate) that a computer processor mounts onto that also connects to the motherboard. The work, however, was not very fulfilling and I started to feel that it was time to shift the direction of my career path.
Starting in 2016, I began learning Python on my own time. A friend of mine was learning data science at the same time and suggested a Coursera course. While taking the course I was also introduced to a podcast called Partially Derivative — a show featuring a couple of people drinking beers and talking about current data science stories. One of the stories was about a project using satellite photos to predict if ships were illegally fishing or not. My mind was blown and at that point I knew I wanted to transition to a career in data science. I knew it would be difficult to make a career shift even with the eight or so Coursera certificates that I had obtained so far; I decided then to pursue a Master’s program.
When I started my Master’s program in the fall of 2017, my attitude towards education was much different than it was in undergrad. I had gained self-confidence, as well as motivation and drive to continue down my chosen path. This college experience was so much more enjoyable and rewarding from what I remembered academia being like. I deeply appreciated learning about new topics that I found interesting — my grades AND attitude reflected this. I realized that it would be important to have some working experience before graduating and luckily, obtained two back-to-back internships at Apple, where I stayed for nearly two years. To me, the tangible experience in a large tech company was much more important than completing the Master’s program on time.
In 2020, I was nearly finished with my Master’s program but I wanted to bolster my data science skills, grow my portfolio, and increase my network while I still had the flexibility in my schedule to do so. Luckily, my brother Codey told me about the Data Science for All / Empowerment program from Correlation One, which he was accepted to as he was making his own career shift. He was really excited about starting and spoke highly about all it had to offer. After doing my own research on the program, I applied to join as well — it was exactly what I’d been looking for. Aside from getting more practice with my data science skills, the program ended with a group project that would be vital to growing my portfolio.
My group worked on highlighting the social impact of agricultural pollution using the Salton Sea as a case study. We gathered many datasets, including water level, air quality, demographic, and income data for the surrounding communities to show that people of color and those of lower socioeconomic status were disproportionately affected by this problem (this project and a few others can be viewed on my c1-connect profile). The DS4A / Empowerment program gave me a space to not only interact and network with my cohort, but also many industry professionals and recruiters looking to fill data science roles. I was assigned to two TAs — both talented data scientists — who were extremely helpful in answering my career-related questions from their own experiences.
One of my teaching assistants, Matthew Finney — who also became my mentor and friend — introduced me to an internship opportunity to join a data for good/data ethics project with the City of San José Mayor’s Office. This is where I worked while applying to full time roles. Matthew also recommended that I become a TA for the next DS4A cohort. I formally applied and was accepted — it means a lot to me to be able to help the community in an instructional capacity. I look forward to learning other people’s stories on what led them to DS4A.
Looking back at this point I can confidently say that it has been a long, winding, and adventurous road. I really took this transition slowly — I was lucky enough to have the option thanks to the support of my wonderful partner, Emily. The next big step for me will be to become a full time data-scientist. I plan on continuing to pay it forward where I can and keep learning. If you’ve made it this far and you’re looking to make a career change yourself, I hope that my story inspires you to do so. After you have an unshakeable idea of what you want to do, GO FOR IT! A year from now, you’ll wish you started today. Good luck!