From Economics to Bioinformatics: My Unconventional Path

Navigating Self-Learning, Embracing Change, and Driving Change Through Data Science

Photo by Christina Morillo

Nearly three years ago, I walked onto my college campus, excited to start my economics major and ready to become an economist. Now, in August 2023, I will be starting my data science master’s program, researching bioinformatics.

Shifting Interests and Newfound Passions

In the fall of 2021, I took the required Data Skills for Economics course. During one of the first programming assignments, I found myself genuinely excited by programming and data science. At that moment, I did not realize that this budding interest would completely change my career aspirations: from becoming an economist to becoming a data scientist, eventually steering me towards a specialization in bioinformatics.

Overcoming Insecurities and Embracing Challenges

Despite having no prior coding experience, I was drawn to the potential of programming and was eager to find my place within it. This newfound interest stirred up waves of insecurity. I was conscious that many of my peers had started pursuing their interest in technology in high school. This realization was further compounded by a paradigm-shifting revelation: I had been completely unaware of the power of self-education and the potential to significantly improve my career prospects through independent learning. The traditional path of ‘college begets job’ was no longer the only route available to me. Although I was only 19, I found myself asking, “Was I starting too late? Could I ever catch up?” This uncertainty did not deter me but instead motivated me to take up the challenge and venture forward. This was the start of my self-directed learning journey, one that continues to shape my professional life.

Interestingly, my first foray into self-learning led me to web development. With a myriad of online resources at my disposal, I dove into HTML, CSS, JavaScript, and React, and even landed my first internship as a front-end developer. This gave me a taste of the tech world and showed me that the ‘unconventional’ path of self-learning could indeed lead to real opportunities.

However, as I progressed, I realized that my true interest lay not in building websites but in unearthing valuable insights hidden within vast amounts of data. Thus, the uncertainty about my late start did not deter me. Instead, it sparked a motivation to take up the challenge and venture forward into the expansive world of data science. This marked the start of my self-directed learning journey in data science, a journey that continues to shape my professional life.

Charting a New Path

Recognizing that the initial steps into this new field would be largely self-driven, I committed to spending time outside of my full-time economics undergraduate program to learn the skills necessary for a career in data science. Despite a full course load, I immersed myself in topics such as artificial intelligence, machine learning, linear algebra, calculus, and mathematical modeling.

Opportunities and Learning Experiences

By 2022, I had the opportunity to participate in the AWS Artificial Intelligence and Machine Learning Scholars program. This experience not only deepened my knowledge but also provided practical AI experience, amplifying my ambition to forge a career in this field. During this time, I gained a better grasp of complex topics and acquired crucial background knowledge, especially in the mathematical foundations of AI. This was also in this pivotal year that my interest steered towards bioinformatics — a field where biology and data science intersect to decipher the complexities of biological data.

A New Direction and Societal Impact

This new direction made data science even more intriguing, prompting me to enroll in an epidemiology and biostatistics non-degree course in the spring of 2023, just after graduating with my bachelor’s in Economics. This course provided a valuable perspective on various aspects of public health, introduced me to working with healthcare data, and showed me how data science could identify and mitigate healthcare disparities. Realizing the profound societal implications of data science, particularly in bioinformatics and biostatistics, over time, while learning more about what data science could do, I was driven to continue going.

With time, I realized the profound societal implications of data science, particularly in the niche fields of bioinformatics and biostatistics. The more I learned, the more my interest grew. I saw the potential to effect tangible changes, particularly in underrepresented communities, by utilizing data science to improve medical care, such as disease diagnosis and treatment strategies. The alignment of these disciplines with my deeply rooted interest in societal impact steered my academic pursuits and career aspirations toward data science and bioinformatics.

My Journey: An Evolution, Not a Leap

The journey from economics to data science was not a sudden leap but a gradual metamorphosis. This journey was filled with obstacles, yet overcoming them provided valuable insights. Juggling self-learning as a full-time student was a significant hurdle. The absence of a structured pathway was daunting, but these challenges instilled resilience, patience, and perseverance. This personal exploration, though marked by moments of self-doubt and determination, shaped me into a more resilient and adaptable individual, prepared to face the ever-evolving challenges of data science and technology as a whole.

Towards a Bright Future

Today, I stand at the threshold of a new journey as a data science graduate student. My focus is on bioinformatics, particularly genetic data, which forms the basis of my master’s thesis. My ultimate goal is to attain a PhD which was spurred by passion and ambition ignited on this transformative journey.

Reflection and Personal Transformation

Reflecting on this journey, I realize how significantly I have evolved. I am now more of a planner, meticulous in charting my academic and career trajectory. The process of self-learning underscored the value of curiosity, initiative, and dedication.

My transition from economics to data science and now bioinformatics is a testament to the power of self-learning and adaptability. As I strive toward a career as a research scientist, I am prepared to push the boundaries of technology and knowledge. I am driven by my commitment to bioinformatics, not just for the prospects of harnessing the full potential of data science but also for driving change and improvements in life sciences.

My unconventional journey, underpinned by self-learning, resilience, and determination, has equipped me to face the dynamic challenges of bioinformatics. My experiences and commitment to societal change have primed me to work in a rewarding career: I am passionate about impacting lives directly through the power of bioinformatics.

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