Lee Bailey
About our Founder
Lee Bailey is an emerging expert in the field of algorithmic trading and the founder of Grizzly Bulls, a leading algorithmic trading service. With a passion for technology, finance, and data-driven decision-making, Lee has dedicated his career to the development and application of innovative trading strategies.
Lee's deep understanding of software engineering and machine learning has been instrumental in creating robust and high-performing trading models. His extensive knowledge of financial markets, coupled with his technical expertise, has allowed him to devise effective solutions that generate consistent returns.
Prior to founding Grizzly Bulls, Lee co-founded Dragonboat, a highly successful product and portfolio management SaaS. With a strong academic background, Lee holds both a Bachelor's and a Master's degree in computer science with an emphasis on machine learning from Wake Forest University.
Lee's fascination with economics and finance began at a young age and has driven his pursuit of a career at the intersection of technology and trading. Through his years of experience as a software engineer and his continuous exploration of algorithmic trading strategies, he has gained invaluable insights into the intricacies of the financial markets.
Outside of his professional endeavors, Lee enjoys spending time with his wife, Heather, and their beloved pets, Abu the dog and Lissa the cat. They reside in the beautiful coastal town of Santa Rosa Beach, FL, where Lee finds inspiration from the serene surroundings to further innovate and contribute to the algorithmic trading community.
Lee Bailey's expertise, passion, and commitment to excellence make him a leading authority in the field of algorithmic trading. Through his work at Grizzly Bulls and his various contributions to the trading community, Lee continues to empower traders with the tools and knowledge they need to thrive in the dynamic world of algorithmic trading.
Highlighted Articles
I've been trading for more than 15 years. In early 2020, I decided to apply my knowledge of markets, machine learning and engineering to build our first algorithmic trading models.