Hi, I’m Xavier, a multidisciplinary professional navigating the convergence of finance, statistics, and information systems. My career is defined by a refusal to be pigeonholed into a single discipline; I am simultaneously a Statistician, an Economist, and a Certified Public Accountant (CPA). I am passionate about uncovering the mathematical logic behind complex systems, whether they are market fluctuations, auditing algorithms, or musical compositions.

My research interests

My intellectual curiosity is deeply rooted in Applied Mathematics and Operations Research. I am fascinated by the potential of mathematical programming languages, such as AMPL, to solve intricate optimization problems in logistics and finance. Beyond the traditional scope of economics, I have a profound interest in Algorithmic Music and Computational Arts. I actively explore the intersection of art and code, utilizing tools like Pure Data for real-time graphical programming and LilyPond for automated music engraving. My goal is to investigate how stochastic processes—typically used for risk modeling—can be repurposed to generate expressive, non-deterministic musical structures, bridging the gap between rigid statistical models and creative fluidity.

My background and history

My academic journey has been rigorous and diverse, characterized by a pursuit of excellence that crosses borders. I earned my Master’s degree in Statistics and Operations Research from the Universitat Politècnica de Catalunya (UPC) in Barcelona, Spain. This was a pivotal period in my career, made possible after I was awarded a competitive scholarship based on academic merit, which allowed me to specialize in advanced quantitative methods in Europe.

Prior to my specialization in data science, I built a strong foundation in the financial sector. I hold a Bachelor of Science in Accounting and Auditing, which granted me the CPA designation, and a degree in Economics. This dual background gave me years of experience in financial auditing, tax compliance, and regulatory frameworks. However, I realized that traditional methods were often insufficient for modern data volumes. This drove me to transition towards computer science and programming. Today, I combine my domain expertise in tax and finance with modern technical skills in Python, R, and Linux systems. I have also dedicated time to academia, teaching courses on Operations Research and Statistics, where I strive to help students visualize the powerful narrative hidden within raw data.