Quantitative Researcher - Portfolio Optimization - Remote

About the role

Design and implement scalable, multi-period portfolio optimization frameworks that account for transaction costs, slippage, and other market frictions. Develop intraday trading strategies and execution algorithms, and monitor model performance in live trading. Requires a strong quantitative background, typically a master's or PhD in applied mathematics, operations research, computer science, or a related field, along with experience using MOSEK or other optimization frameworks. Candidates should understand intraday trading and transaction cost modeling, have Python and/or C++ programming skills, and be familiar with real-time data processing and integrating optimization routines into production trading systems.