A Quest for Understanding
It all began one day at the kitchen table at my friend’s apartment. This was long before I ever heard the words data science, and before I knew anything about conducting research experiments and applying statistcal analysis. Back then I had become interested in human nutrition and happened to come across a presentation given by Robert Lustig, a pediatric endocrinologist at the University of California San Francisco who specializes in childhood obesity research. Using results from biochemical experiments, he skillfully explained how different forms of sugar molecules are metabolized differently based on the chemical structure of the molecule and the subsequent consquences this can have on our health. He showed a figure of what I later learned was the TCA cycle and I was instantly hooked. He somehow crafted the data into this compelling narrative that forever changed how I saw sugar. I had no idea what biochemistry was at the time but I knew from then on I wanted the ability to do what he had just done.
Years later, I understand now what captured my imagination in this moment; it was the ability to draw insights from the observations one make’s about the world. At that time I wanted to know:
1) How he was able to make those conclusions?
2) How did he know they were accurate?
3) What information did he use?
4) How did he bring it all together to craft this compelling story?
From that moment on, I knew I wanted to make sense of the world in this way. This quest has led me down a long, windy and intellectually stimulating path into the world of data, observation, experiment, scientific research and eventually into the data science field.
Data Science for Social Good
Our world faces many challenges in the coming years with climate change, affordable housing, sustainable food production and ensuring dignified livelihoods with looming threat of automation along with a host of others. If implemented thoughtfully and ethically, data science methods can be used as a powerful toolkit to help address these issues. My ultimate professional goal is to make contributions to better understand our world, inform choices about our future, improve the human condition, protect the environment and foster sustainable stewardship. I found the tools of data science the most compelling way for me to achieve that goal.
The Only Constant is Change
I figured out towards the end of my undergraduate career that my mind tends to wander if not given a hard problem to focus on. Data science is full of hard and interesting problems to solve. So the job never gets boring and its constantly changing. This isn’t a field where you can learn something once and be done learning for the rest of your career. New analytical methods are always being invented, new tools developed every day and more and more data is constantly being generated. It’s a field of constant change. Sometimes that can be exhausting and a challenge to keep up with the sheer pace of it all but the upside is the near constant stream of datasets to analyze and insights to be uncovered. For someone like me who has a fondness for novelty, there are endless things to study to satisfy my curiosity. My data science toolbox gives me the ability to dive into whatever I want.
Into Places Unknown
Since the field is constantly changing I don’t know exactly where my career will take me in the future. Of course I can plan ahead, but there’s no way I can know for sure. There are some fields where what you are doing today will not look much different 10 or 15 years from now. This isn’t the case for data science as the term hasn’t even been around for 20 years (at the time of this writing). At times the uncertainty can cause some trepidation; but mostly I find the thought of it exhilarating. I may not know what the future holds but I know my data science career will give me the flexibility and adaptability to navigate whatever comes next.
I hope you enjoyed reading this post.
