My career is defined by the intersection of rigorous analysis and aesthetic composition. With a background that spans Data Analysis, Backend Development, and Full-Stack Engineering, I solve complex problems by looking for structured simplicity.
Holding a Master's in Economic Analysis & Machine Learning, I utilize Python for sophisticated data modeling and deploy algorithms for real-world impact, such as building personalized recommendation engines and optimizing customer conversions. My work philosophy is anchored in "existential aestheticism," seeking to build digital environments that are exposed but safe—meaning my systems are transparent, highly performant, and reliable.
My four years working in the contemporary art environment and my passion for analog film photography have instilled a core technical philosophy: I prioritize clean architecture and the strategic, structured presentation of information. I am now channeling this expertise into marine biology preservation. My objective is to leverage advanced Full-Stack, Data, and Machine Learning capabilities—from building robust data ingestion pipelines (like those for oceanographic APIs) to deploying predictive ML models (for applications such as coral health indexing)—to create scalable, high-impact tools that directly support environmental conservation efforts. I deliver systems that are financially optimized, technically robust, and designed with the precision required for critical scientific data.
