How does someone turn a childhood love of numbers into a real trading impact?
My path started early with a deep fascination for numbers. This passion drove me to pursue a dual degree in Computer Science and Mathematics at Washington University in St. Louis. I dove into topics like machine learning, stochastic processes, and financial mathematics while mastering programming languages such as Python, SQL, Java, and R.
At Wolverine Trading, I put theory into practice. I analyzed thousands of options trades and built SQL-based ETL pipelines that improved participation rates through specific routing optimizations. Additionally, I've spent two years conducting machine learning research at WashU, focusing on topics like Kalman filters, computer vision, and reinforcement learning.
I hope to continue building my technical skills in an increasingly data-driven, numbers-backed world. I would love to join a quantitative team where I can help develop and implement various trading strategies and models. The opportunity to grow with a fast-paced organization that values technical excellence, collaboration among colleagues, and continuous learning strongly appeals to me.
