Portfolio Manager - US Systematic Equities

Key Responsibilities

• Lead and contribute to the firm’s quantitative research efforts, with a focus on alpha generation, portfolio construction, and risk modeling for U.S. equities.
• Expand research capabilities by identifying and integrating new datasets, economically grounded factors, and innovative analytical approaches.
• Champion the thoughtful adoption of machine learning and emerging AI techniques (including LLMs) to enhance signal generation and investment insights.
• Communicate research findings, portfolio positioning, and performance insights to internal stakeholders and clients.
• Evaluate model outputs alongside real-time market information, exercising judgment in interpreting signals, identifying dislocations, and refining positioning within a systematic framework.
• Oversee daily portfolio implementation, including rebalancing, trade review, and execution oversight, ensuring alignment with model outputs and portfolio constraints.
• Analyze portfolio performance and attribution, identifying key drivers of return and risk, and translating insights into model refinements and positioning.
• Generate market-driven insights from company-specific news and evolving macro conditions to inform portfolio decisions and research.
• Mentor a small team of research analysts, guiding alpha research across U.S. markets and related investment universes.

Qualifications

• 10+ years of experience in quantitative investing, with demonstrated leadership in equity research (U.S. experience strongly preferred).
• Deep expertise in alpha research, factor modeling, or machine learning applied to financial markets.
• Proven ability to lead research initiatives and deliver innovative, economically grounded investment insights.
• Excellent communication and presentation skills, with the ability to convey complex ideas to both technical and non-technical audiences.
• Ability to operate efficiently in a fast-paced, collaborative environment and manage competing priorities.
• Advanced degree in a quantitative discipline such as Finance, Economics, Math, or Engineering.
• Nice to have (preferred but not required): Experience across multiple regions or asset classes, Strong understanding of data architecture, research platforms, and production systems, Understanding of the U.S. market microstructure, Good programming skills, particularly in Python, CFA or related designation.