Lead Quantitative Researcher - Portfolio Optimization
Location: New York, Los Angeles, or San Francisco
- Lead Optimization Research: Design and implement advanced optimization models, including convex, non-linear, and integer programming, to support portfolio construction and capital allocation.
- Develop Systematic Strategies: Leverage your expertise in portfolio analysis and trading strategies to build scalable, rules-based frameworks for portfolio replication and optimization.
- Bridge Theory and Practice: Apply quantitative frameworks to real-world investment challenges, aligning model-driven insights with the firm's fundamental research process.
- Collaborate Across Teams: Work closely with investment professionals, governance bodies, and technology partners to embed optimization tools into the investment lifecycle.
- Drive Innovation: Explore new research directions, contribute to strategic initiatives, and foster a culture of continuous learning and improvement.
- Educate and Influence: Represent the firm's optimization capabilities internally and externally, translating complex technical concepts into actionable insights.
- PhD in Operations Research strongly preferred; alternatively, a PhD in a quantitative field (e.g., Financial Engineering, Applied Mathematics, Computer Science) with demonstrated expertise in optimization.
- 10+ years of experience in portfolio optimization, systematic portfolio construction, or related quantitative research roles.
- Deep knowledge of optimization techniques and their application to long-only investment strategies, including awareness of implementation trade-offs and constraints.
- Proficient in optimization programming tools such as CPLEX, MUREX, and GUROBI, as well as statistical and coding languages like Python, R, or MATLAB.
- Familiarity with fundamental equity research, econometrics, and modern financial theory, including asset pricing, portfolio theory, factor models, and machine learning.
- Strong analytical and strategic thinking skills, with the ability to translate complex research into practical, scalable solutions.
- Excellent communication skills, capable of influencing both technical and non-technical stakeholders.
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