Quantitative Research Associate - Systematic Portfolio Construction

About the role

We are seeking a Quantitative Research Associate to join our Quantitative Research and Analytics group (QRA) at Capital Group (CG).

Responsibilities

• Deliver high-impact research on portfolio construction and optimization.
• Develop and maintain relevant quantitative models and frameworks.
• Partner with QRA leadership, Portfolio Strategy Management leadership, and Investment Group associates to understand and execute on quantitative research and analytical priorities.
• Work collaboratively with members of the QRA team in a rigorous peer-reviewed approach to quantitative research and support the team with portfolio optimization expertise.
• Respond to deadline-driven requests requiring quantitative analysis.
• Participate in the ongoing development of quantitative research processes at CG.
• Communicate results and recommendations in a form that meets the needs of the listener.
• Help develop computing environments to support research and research-driven processes in a collaborative research environment.

Requirements

• Advanced knowledge of optimization methods (including convex, non-linear, and integer programming) and systematic portfolio construction methods, with a minimum of 5 years of relevant experience.
• Excellent systems and computer skills, including demonstrable expertise with quantitative programming languages (e.g., Python, Julia, or R) and with optimization software (e.g. Gurobi or Mosek).
• A minimum of a basic knowledge of fundamental research, econometrics and modern financial economic theory: e.g. asset pricing, portfolio theory, factor risk models, and machine learning.
• An advanced degree (MFE, MSc, PhD) in a mathematically robust discipline (e.g., mathematics, economics, operations research) or equivalent experience.
• Excellent quantitative research skills.
• Advanced communication skills – the ability to synthesize issues into solutions, translate complex concepts into simple language, and engage across different audiences.
• Self-motivated, takes initiative, and demonstrates commitment to continuously improve skills and self.
• Curious about financial markets, optimization and portfolio construction, and always learning something new.

Qualifications

• Minimum of 5 years of relevant experience in quantitative research and portfolio optimization.
• Advanced degree (MFE, MSc, PhD) in a mathematically robust discipline (economics, operations research, etc.) or equivalent experience.
• Expertise in optimization methods, including convex, non-linear, and integer programming.
• Knowledge of portfolio optimization, trading strategies, and portfolio analysis.
• Experience working with quantitative programming languages (Python, Julia, R) and optimization software (Gurobi, Mosek).
• Basic understanding of fundamental research, econometrics, and modern financial economic theory.
• Strong communication skills, able to convey complex ideas clearly and effectively.
• Ability to work independently and manage multiple tasks simultaneously.
• Passion for learning and staying updated with the latest developments in quantitative finance and portfolio management.

Skills

• Quantitative programming languages (Python, Julia, R)
• Optimization software (Gurobi, Mosek)
• Portfolio optimization and trading strategies
• Systematic portfolio construction methods
• Machine learning and econometrics
• Effective communication skills
• Continuous learning and improvement mindset

Benefits

• Competitive salary range based on location: $159,354 - $254,966 in Southern California, $185,833 - $297,333 in San Francisco, $168,924 - $270,278 in New York.
• Annual performance bonus.
• Capital’s annual profitability bonus.
• Company-funded retirement contribution.
• Matching gifts for charitable contributions.
• On-demand professional development resources.

Pay

• Southern California: $159,354 - $254,966
• San Francisco: $185,833 - $297,333
• New York: $168,924 - $270,278

Schedule

• Full-time position.

Application

If you are interested in applying, please review this job posting and apply now to move to the next step in our recruiting process. If this role isn't what you're looking for, check out our other opportunities and join our talent community.