Quantitative Analyst – Systematic Portfolio Construction – Spc

Quantitative Analyst – Systematic Portfolio Construction – Spc

Requirements

• Detailed knowledge of portfolio optimization (including convex, non-linear, and integer programming) and systematic portfolio construction methods, with a minimum of 10-15 years of relevant experience.
• Command of the strengths, weaknesses and implementation issues related to standard portfolio construction techniques as applied to long-only investment strategies.
• Working knowledge of fundamental equity research, econometrics and modern financial economic theory: e.g. asset pricing, portfolio theory, factor risk models, and machine learning.
• Excellent quantitative research skills, as evidenced by an advanced degree (MFE, MSc, PhD) in a mathematically robust discipline (e.g., mathematics, economics, operations research) or equivalent experience, ideally with a record of written research.
• Exhibit advanced communication skills – the ability to synthesize issues into solutions, translate complex concepts into simple language, listen actively and reflect.
• Strong consulting and relationship building skill set; the ability to engage with engineers, investment professionals, and other partners; communicate in multiple formats/forums, and deliver solutions that address business needs.
• Self-motivated, take initiative, and demonstrate commitment to continuously improve skills and self.
• Excellent systems and computer skills, including demonstrable expertise in quantitative programming languages (e.g., Python, Julia, or R) and working knowledge of optimization software and libraries.

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 identify quantitative research and analytical priorities.
• Translate priorities into coherent approaches to resolve problems and manage problem statements from inception to completion.
• Work collaboratively with members of the QRA team in a rigorous, peer-reviewed and hypothesis-driven approach to quantitative research, and support the team with domain expertise.
• Communicate results and recommendations in a form that meets the needs of the listener.
• Engage consistently with our technology partners and help develop computing environments to support research and research-driven processes in a collaborative research environment.

Preferred Qualifications

No preferred qualifications provided.