Quantitative Researcher - Entry Level 2027

Belvedere Trading is a leading proprietary trading firm headquartered in downtown Chicago. Its traders provide liquidity to the market through market-making activities and trade commodities, interest rates, exchange-traded funds (ETF), and equity index options. The firm invests in its proprietary technology and continually re-engineers, optimizes, and maintains its trading models and software systems. Sponsorship: Yes. Amount of Travel Required: None. Regular and reliable attendance during business hours with the ability to be on-site prior to the start of business on occasion. The SIE and Series 57 licenses are required for trading positions and certain engineering roles; Belvedere Trading will provide study materials and dedicated onboarding time to support obtaining them.

Responsibilities

Work closely with traders to prioritize hypotheses, interpret results, and translate research into deployable trading strategies; Design, test, and deploy quantitative models that drive pricing, risk, and execution in market-making and systematic trading; Build, improve, and maintain research tools (e.g., Python, Jupyter) for testing, backtesting, validating, and monitoring models and strategies; Collaborate closely with traders, technologists, and senior quantitative researchers to ensure strong alignment between research insights and production trading decisions; Continuously monitor and enhance existing models and strategies, adjusting for market dynamics, data drift, and performance deviations; Combine statistical rigor, market microstructure knowledge, and engineering fluency to deliver robust edge and provable PNL

Requirements

Advanced degree (Master's or PhD) in a quantitative field such as Mathematics, Statistics, Physics, Financial Engineering, or a related discipline; 2+ years of experience in quantitative research in trading or a related field; Strong proficiency in Python or C++ for model research, prototyping, and production implementation; experience with version control and collaborative development workflows; Experience working with large datasets, statistical modeling, or algorithmic workflows; Demonstrated ability to analyze model outputs and communicate results clearly to both technical and non-technical stakeholders; Strong collaboration skills with developers, traders, and other researchers in a fast-paced, iterative environment; Intellectual curiosity, problem-solving ability, and a pragmatic approach to research that balances innovation with production impact