Quantitative Analyst

Private Markets Quant Analyst will design and maintain customized investment strategies across the firm’s global alternatives platform, including real estate, infrastructure, renewable power, private equity, and credit.

The team partners closely with institutional and wealth clients to develop tailored portfolio solutions that align with specific objectives such as income generation, inflation protection, and long-term capital appreciation.

Experience with product development, portfolio construction, investment selection and capital formation, structuring bespoke mandates, commingled vehicles, and strategic partnerships is sought

Responsibilities:

• Design and implement portfolio optimization frameworks for private market portfolios across multiple asset classes.
• Develop optimization models that incorporate illiquidity, capital calls, distributions, pacing, vintage diversification, sector/geographic constraints, and leverage.
• Develop quantitative models for expected returns, risk, cash flow forecasting, and correlations across private market investments.
• Build simulation engines using Monte Carlo and scenario analysis to evaluate portfolio outcomes under different economic environments.
• Work with private market data providers (Cambridge, MSCI/Burgiss/Preqin)
• Contribute to the build out of private market risk measurements (factor models, de-smoothing volatility, manager/investment level dispersion, stress testing)
• Work closely with Portfolio Managers, fundamental investment analysts, and risk management
• Thought leadership pieces and whitepapers on private portfolio construction, design, and risk assessment

The Candidate:

The successful candidate will possess the following:

• Bachelors or Masters degree in Mathematics, Statistics, Physics, Computer Science, or another highly quantitative field
• 4+ experience within a leading private markets investment manager, pension fund, sovereign wealth fund, endowment, OCIO, or asset manager.
• Strong understanding of private market cash flow dynamics including capital calls, distributions, NAV evolution, commitment pacing, liquidity forecasting
• Strong programming skills within SQL, Python and experience with portfolio optimization software preferred
• Experience working with factor models used in portfolio construction and risk management (Bloomberg, Barra, Axioma, etc..)
• Knowledge of portfolio optimization techniques used to target different outcomes (yield, volatility, MOIC maximation, downside protection) with complex constraints.
• Effective communicator, both oral and written, with ability to present with clarity, precision and conviction
• Experience working with large datasets and data visualization tools (Tableau, Python, R)