Seeking a highly analytical and intellectually curious Quantitative Researcher with a PhD in a quantitative field such as Mathematics, Statistics, Computer Science, Physics or Engineering. In this role, you will design, develop, and evaluate statistical and machine learning models to drive systematic trading strategies across global markets. You will work closely with portfolio managers, data engineers, and technologists to translate research insights into alpha.
Key Responsibilities
• Conduct end‑to‑end research on alpha signals using statistical modeling, machine learning, time‑series analysis, and portfolio optimization techniques.
• Explore large, diverse, and novel datasets to uncover predictive patterns that can be transformed into trading opportunities.
• Design and test systematic strategies through rigorous backtesting, simulation frameworks, and advanced statistical validation.
• Collaborate with engineering teams to deploy research into scalable, real‑time trading environments.
• Improve research tooling, workflows, and model evaluation frameworks to accelerate discovery and deployment.
• Continuously monitor model performance and propose enhancements based on empirical results.
• Present research findings to investment leadership through clear, structured analysis and data visualization.
Qualifications
• PhD in a quantitative discipline (e.g., Mathematics, Physics, Statistics, Computer Science, Operations Research, Engineering).
• Strong background in probability, statistics, stochastic processes, optimization, and/or machine learning.
• Proficient programming skills in Python; experience with scientific computing libraries (NumPy, pandas, SciPy, PyTorch, TensorFlow) is a plus.
• Experience with large‑scale data analysis and empirical research; familiarity with cloud or distributed systems is advantageous.
• Ability to think independently, form hypotheses, and validate them through disciplined experimentation.
• Strong communication skills and the ability to collaborate in a fast‑paced research and trading environment.
