Job responsibilities

• Research and develop novel alpha signals using traditional and alternative data sources to enhance return forecasting models.
• Improve return forecasting models and portfolio construction frameworks for global equity markets, applying reinforcement learning and advanced machine learning techniques.
• Apply statistical, econometric, and machine learning methods to large, complex datasets to extract actionable insights.
• Collaborate with technology teams to integrate research models into production systems and ensure robust implementation.
• Partner with portfolio managers and stakeholders to translate quantitative research into investment decisions.
• Stay current with academic and industry developments in quantitative finance, machine learning, and data science.
• Present complex research findings clearly to both technical and non-technical audiences.
• Contribute to a collaborative team environment and support continuous learning and innovation.

Required qualifications, capabilities, and skills

• PhD in machine learning, computer science, statistics, or a related quantitative discipline; specialization in reinforcement learning highly desirable.
• 0–3 years of experience in quantitative research, data science, or a related field (industry or academic).
• Strong programming skills in Python and experience with machine learning libraries.
• Familiarity with quantitative modeling, portfolio construction, and equity markets.
• Experience working with large, complex, and alternative datasets.
• Excellent verbal and written communication skills, with the ability to present complex ideas to technical and non-technical audiences.
• Demonstrated ability to work effectively in a team environment.
• Strong problem-solving skills, intellectual curiosity, and ability to drive research projects independently.

Preferred qualifications, capabilities, and skills

• Experience integrating research models into production investment systems.
• Background in developing and implementing reinforcement learning techniques in finance.
• Experience collaborating with portfolio managers and technologists.
• Track record of publishing or presenting research in quantitative finance or machine learning.