About Me

Professional Journey

I started my career in quantitative finance in 2020 as a Junior Quantitative Analyst, where I quickly discovered my passion for combining mathematical modeling with advanced technology. Over the past four years, I've progressed to a full Quantitative Analyst role, focusing on energy market forecasting and machine learning infrastructure.

My work centers on developing sophisticated quantitative models for energy trading, where I leverage time-series analysis, statistical modeling, and machine learning to predict market behavior and optimize trading strategies. I process millions of data points daily, building systems that need to be both mathematically sound and operationally robust.

Technical Expertise

Beyond traditional quantitative analysis, I've developed deep expertise in machine learning infrastructure, particularly in deploying and optimizing large language models across multi-GPU setups. I'm fascinated by the challenge of making powerful AI models run efficiently in production environments, where every millisecond of latency and every megabyte of VRAM matters.

My technical toolkit spans Python for quantitative modeling, PyTorch for deep learning, Docker for containerization, and CUDA for GPU optimization. I'm equally comfortable analyzing financial data, training neural networks, or debugging infrastructure issues in production systems.

Problem-Solving Approach

I approach problems methodically, starting with a deep understanding of the underlying mathematics and economics before implementing technical solutions. Whether it's forecasting energy prices or optimizing ML inference pipelines, I believe in building systems that are not just technically impressive, but practically valuable and maintainable.

Continuous learning is central to my professional philosophy. The intersection of quantitative finance and machine learning is rapidly evolving, and I stay current through hands-on experimentation, contributing to open-source projects like LTX Video, and pushing the boundaries of what's possible in production ML systems.

Beyond Work

Outside of quantitative finance and ML, I enjoy exploring technology through personal projects. I've built a comprehensive home automation system that integrates IoT devices with custom 3D-printed enclosures, demonstrating my ability to bridge software and hardware. I also enjoy photography, which provides a creative outlet and a different way of seeing patterns and structure in the world.