Asset Management - Quantitative Research Analyst

J.P. Morgan Multi-Asset Solutions draws upon over 40 years of experience in managing multi-asset class portfolios. With over 100 investment professionals worldwide, we manage over $200 billion in AUM across flexible, outcome-oriented, quantitative and convertibles strategies, for a broad range of clients including institutions, advisors and individuals. Our group provides solutions to meet a wide need of investment goals including generating income, preserving capital, managing volatility, asset-liability management, and investing for retirement. The group’s approach to multi-asset investing is based on a disciplined and rigorous approach integrating qualitative and quantitative components.

Quantitative Solutions Team

The Quantitative Solutions Team within the Multi-Asset Solutions (MAS) team is a sub-team that supports portfolio managers through robust quantitative portfolio analysis and ongoing product related research, and manages global macro investment strategies, global tactical asset allocation accounts and alternative beta strategies. As part of this team you will be focused primarily on three aspects of MAS’s investment process: strategic asset allocation, tactical asset allocation, and portfolio construction. Members of our team also contribute to the firm-wide development of Long Term Capital Market Assumptions and designing of risk controlled portfolios.

Job Responsibilities:

• Research and implement systematic alpha models for equities, rates and FX
• Contribute to development of portfolio construction and risk management infrastructure for the multi-asset team
• Present new research and weekly outputs of the models at various internal forums
• Responsible for day-to-day management of the systematic models
• Liaise with portfolio managers to facilitate systematic execution of the models across various portfolios

Qualifications

• Some work experience in the financial markets and preferably a strong understanding of multi-asset portfolios
• Preferably a master’s or PhD degree in a quantitative discipline such as mathematics, statistics or engineering and with decent foundation in finance and economics (CFA or equivalent)
• Strong coding and data analysis skills are required with a preference for Python experience (or equivalent in R or Matlab)
• Experience with financial databases, portfolio optimization techniques and modern machine learning techniques are a plus
• Clear and effective communication skills (both verbal and written), especially for presenting complex quantitative research