Artificial Intelligence Researcher

A leading global systematic investment firm is seeking an exceptional AI Scientist to join its Artificial Intelligence team. The successful candidate will conduct cutting‑edge machine‑learning research and develop innovative models, predictive signals, and AI‑driven tools used throughout the investment process.

This position is suited to a highly creative researcher who combines strong academic foundations with practical problem‑solving skills and an interest in applying advanced AI techniques to financial markets.

• Conduct machine‑learning research to improve multiple stages of the systematic investment process.
• Develop predictive and trading signals using innovative machine‑learning techniques.
• Apply large language models and agentic AI technologies to research, develop, and test new trading signals and investment algorithms.
• Design and implement state‑of‑the‑art deep‑learning architectures.
• Develop machine‑learning methods for signal compression, combination, and portfolio integration.
• Build scalable modeling frameworks and research tools for investment professionals.
• Run experiments, conduct statistical inference, and evaluate model robustness and performance.
• Collaborate closely with portfolio managers, quantitative researchers, and engineers to improve investment models and algorithms.
• Translate complex research findings into clear and practical recommendations.

• PhD in Computer Science, Mathematics, Statistics, Machine Learning, or another highly quantitative discipline.
• At least two years of professional or academic research experience applying machine learning to complex problems.
• Outstanding academic record and evidence of strong intellectual ability.
• Demonstrated creativity through original research, publications, inventions, or the development of novel methodologies.
• Advanced knowledge of machine learning, deep learning, statistical inference, mathematical optimization, or numerical solvers.
• Strong programming skills in Python and C++, with practical experience using PyTorch.
• Experience designing experiments, validating models, and interpreting statistical results.
• Familiarity with professional software‑development practices, including Git, continuous integration, automated testing, and code review.
• Excellent analytical judgment, attention to detail, and problem‑solving ability.
• Strong communication skills, with the ability to explain sophisticated technical concepts clearly.
• Prior financial‑market experience is advantageous but not essential.