Background
I am a data science graduate student with strong skills in building intelligent systems and solving business problems using machine learning, data modeling, and modern AI techniques. I have experience applying data analytics, statistical modeling, and real-time data pipelines, as well as working with graph neural networks and full-stack development using tools like Supabase, OpenAI, and Cursor AI.
Bio
Before transitioning into data science, I worked in hospitality and briefly in animation, gaining experience in fast-paced, creative environments. My background in music—as a composer and producer—instilled in me skills like pattern recognition, creative problem-solving, and persistence, which continue to shape my approach to data and technology.
I returned to school to pursue computer science, earning my associate’s degree before transferring to Fairleigh Dickinson University, where I deepened my technical expertise with the support of scholarships and grants.
Initially eyeing cybersecurity, I shifted focus after a professor’s encouragement led me to data analytics — and everything clicked. In data science, I found a field that unites my creativity, curiosity, and analytical mindset, offering both purpose and sustainability.