My interest in quantitative finance grew out of a strong olympiad background in mathematics and economics. Among my academic achievements are winning the North Countries Universities Mathematical Competition and the National Economics Olympiad, which also earned me a full merit scholarship. This background shaped my interest in mathematics, machine learning, and quantitative problem-solving. I am particularly interested in systematic trading, statistical modeling, and the use of machine learning in financial markets. In my quantitative research role, I developed algorithmic trading strategies and studied alpha signals and statistical relationships in cryptocurrency markets. Previously, I worked as an ML Engineer at Sberbank, Russia鈥檚 largest bank. I built a text-to-image search pipeline, developed an LLM chatbot with long-term memory, and built a resume-to-job matching system deployed to production. My work involved Python, PyTorch, NLP, embeddings, vector databases, retrieval systems, and large-scale data processing. I am seeking opportunities in quantitative research and trading where I can apply my mathematical background, programming skills, and machine learning experience to real market problems.
