Senior Portfolio Manager

Ph.D. in Computer Science, Engineering, Applied Mathematics, or a related quantitative field
5+ years of experience managing a live portfolio using automated or algorithmic strategies
Strong background in quantitative research, statistical modeling, and signal development
Demonstrated ability to build and maintain a systematic investment process with limited discretionary intervention
Proficiency in programming languages such as Python, C++, R, or similar
Deep understanding of risk management, execution algorithms, and portfolio optimization
Strong communication, analytical, and problem-solving skills with solid reasoning in data driven and theoretical approaches
Active team player motivated by a fast-paced environment and conviction to focus on difficult, long-duration problems that require iteration
Familiarity with machine learning, reinforcement learning, or online learning techniques in trading contexts a plus
Availability to work in a hybrid structure out of our Chicago or Boulder offices

Design, test, and manage automated trading strategies across one or more asset classes including stocks, futures, bonds, and options
Develop and refine quantitative models for alpha generation, portfolio construction, and risk control
Embrace the uncertainty persistent in the marketplace to balance the risk-reward in each individual trade
Monitor and adjust models in production based on performance and changing market dynamics
Collaborate with researchers and engineers to optimize data infrastructure, simulation tools, and execution systems
Provide macro guidance on the exchange-traded portfolio and other private market investments of the family office
Evaluate new data sources to enhance strategy edge
Maintain robust performance attribution and risk reporting

Familiarity with machine learning, reinforcement learning, or online learning techniques in trading contexts a plus