Quantitative Researcher/Developer

As an experienced Quantitative Researcher/Developer, you will be responsible for enhancing and scaling live IBKR TWS algorithms. Your role will involve end-to-end strategy development, including math-driven model design, backtesting, low-latency implementation, and continuous performance tuning. Your key responsibilities will include auditing, troubleshooting, and optimizing existing TWS/IBKR Python strategies for equities, options, and futures. You will also design and deploy high-frequency trading/low-latency strategies using statistical, machine learning, and signal-processing techniques. Additionally, you will employ time-series analysis, probability modeling, VaR, tail-risk, and skewness/drawdown metrics for quantitative analysis. In terms of infrastructure and automation, you will build robust data pipelines, integrate with IBKR's API, and automate end-to-end backtest/live-trade processes. Collaboration with the trading desk to translate research into production-grade code and mentor junior quants will also be a key aspect of your role. The ideal candidate should have at least 5 years of professional experience as a quantitative researcher/developer in electronic equities, options, or futures markets. Deep expertise in IBKR TWS API & Python, high-frequency trading strategies, statistics, mathematics, and experience with US market live-tested algos are required. Proficiency in engineering best practices such as version control, CI/CD pipelines, code review, and performance profiling is essential. Preferred skills include proficiency in Python/C++ for latency-sensitive components, knowledge of cloud infrastructure for scaling back tests, and familiarity with machine learning frameworks for signal generation. For the interview process, you may be asked questions related to algorithm debugging, latency optimization, statistical modeling, risk management, and live strategy examples to assess your skills and experience in quantitative research and development. Overall, this role requires a strong background in quantitative research and development, expertise in algorithm optimization, statistical modeling, risk management, and collaboration with trading desks to drive the enhancement and scaling of live IBKR TWS algorithms.,