Asset Management MAS Program Associate (Quantitative Portfolio Management)

JPMorgan Chase & Co.•New York, NY

About The Position

The Quantitative Solutions team is part of Multi-Asset Solutions (MAS) within J.P. Morgan Asset Management. We manage a broad range of systematic investment strategies, including factor and thematic approaches, in pooled vehicles and for institutions. MAS brings over 50 years of expertise in managing multi-asset portfolios and leverages proprietary JPMAM strategies to deliver customized, cross-asset class solutions tailored to the needs of institutional and retail clients. MAS has more than $400 billion in assets under management, for a diverse global client base. As an Asset Management MAS (Quantitative Solutions) Program Associate on the MAS Quantitative Solutions Portfolio Management and Research team, you will join a team of experienced portfolio managers and researchers, playing a key role in both portfolio management and trading activities. You will advance our investment process through high-impact research and hands-on implementation. You’ll work closely with team members to develop and refine quantitative investment models, focusing on factor-based equity, but with opportunities to work across asset classes. Within our collaborative team, you will translate research insights into actionable strategies and tools. Your work will help shape the future of investment solutions for a diverse range of clients.

Requirements

Bachelor’s in Mathematics, Engineering, Physics, Computer Science, or other STEM discipline.
Proficiency in Python, R, Matlab, or similar programming languages
Process-oriented with strong organizational skills and excellent attention to detail.
Strong analytical and problem-solving skills.
Intellectual curiosity and drive for continuous learning.
Excellent verbal and written communication skills for both technical and non-technical audiences.
Experience with databases and financial data providers.

Nice To Haves

Master’s, or PhD in Mathematics, Engineering, Physics, Computer Science, or other STEM discipline
Understanding of machine learning models and tools.
Experience presenting complex quantitative research to diverse audiences.
Advanced coursework in finance, asset pricing, econometrics, optimization or stochastic modelling.
Demonstrated experience applying machine learning techniques to financial applications.
Collaborative mindset and ability to work effectively across teams.
Ability to remain calm and focused under pressure, with a proactive approach to addressing challenges.

Responsibilities

Implement systematic equity portfolios, including rebalancing, cash management, corporate actions voting and related trading
Execute and monitor flow activity, ensuring efficient trade execution and settlement.
Propose and implement enhancements to the investment process, including automation.
Analyze and communicate the characteristics of systematic equity portfolios, for the benefit of internal and external stakeholders.
Conduct research to enhance quantitative models, including applying machine learning to financial time series and alternative data.
Translate research insights into actionable investment strategies and tools.
Produce marketing collateral, including whitepapers and thought leadership materials, to communicate research findings.